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Article: Helping to Counter the Terrorist Threat using Face Recognition

Forensic Media Analysis Integrated with Live Surveillance Matching

You can download a PDF copy of this article by clicking this link.

 

Against the backdrop of budget constraints, threats from terrorism, organised crime and public disorder continue to rise. Authorities can remain resilient through the targeted application of technology. Advances in face recognition coupled with the mass availability of digital media and continuously cheaper computing provides unique opportunities to enhance the efficiency of forensic investigations to enhance public safety. Processing of digital media can be automated in a virtualised and elastic computing environment to identify and extract actionable intelligence. Processing is scalable, continuous, consistent and predictable. Analysts can focus on investigating and confirming suggested results rather than watching countless hours of media in the hope of stumbling across intelligence. Such a centralised platform can also be used to search in near real-time faces from any number of remote cameras against centralised watchlists of individuals of interest.

1. A Need for Enhanced Safety and Operational Efficiency

Risks are increasing. Recent events demonstrate that the threat landscape is substantial and becoming more fragmented, consisting of a greater number of smaller and less sophisticated plots. The targeted application of technology can play a key role in improving the efficiency of our police and intelligence agencies and maintaining readiness to both disrupt and respond to major events.

2. A Relentless Increase in Digital Media

The increase in media is relentless. Law enforcement and intelligence agencies have amassed large collections of video and photographic information from multiple sources such as:

  • Digital Forensics (confiscated phones, computers, flash drives etc).
  • Open Source Intelligence (Internet and Dark Web).
  • Crowd- sourced from members of the public (HD cameras on mobile phones are ubiquitous).
  • Police Body Worn Video.

When tragic events or social disorder occur, investigators have a long and arduous task of reviewing countless hours of media, generally with a varying degree of concentration and scrutiny.

A solution that minimises manual effort in the extraction of actionable intelligence from amassed media by automating this process with a consistent and repeatable level of scrutinywill deliver concise and consistent information in a fraction of the time taken by operators undertaking the task manually.

3. An Automated Media Processing and Exploitation Solution

Police, intelligence and other public order agencies can benefit from the application of a powerful media processing solution designed to ingest, analyse and index, in an automated fashion, very large quantities of media from multiple sources to transform them into usable assets. Utilising virtualised and elastic computing environments enables the platform to be rapidly scaled up and down in response to unfolding events.

Once processed, agencies can analyse and make use of the extracted assets and manage them in a centralised repository of information. Data links, associations and metadata inferences can be managed across the whole dataset by multiple users from a single common user interface. Backend processing services are run in a cloud-computing environment, the capacity of which can be configured and incrementally scaled up and down to meet an organisation’s changing demands; peaks arising from specific events can be easily accommodated.

Features include:

  • Automatically find, extract and index faces to enable biometric and biographic searching of media.
  • Create and manage watchlists of people of interest.
  • Find and cross-reference all media instances in which a person of interest has been seen.
  • Identify, locate, and track persons of interest, their associates and their activities across all media.
  • Discover, document and view links between people of interest, their activities and networks.
  • Use of metadata (including geo data) to enhance investigations and association of data.
  • Integration into existing system environments, databases and components.

3.1  Incorporating Other Detection Capabilities

In addition to face recognition, other detection engines can be incorporated, such as:

  • Biographic filtering and Fuzzy Match capability.
  • Automatic Number Plate Recognition. (ANPR)
  • Voice Biometrics.
  • Object / Logo Recognition.

Vendor independence allows the use best-of-breed algorithms. Newer and better algorithms (COTS and GOTS) can be plugged in without having to replace the entire platform.

3.2  Working with Geo-Location Data

An increasing amount of media is captured on devices affixed with location determining technology. Often, this geo-location data is incorporated into the media metadata, thereby providing potential to further enhance the analysis of media. Geo-location can be used to:

  • Compartmentalise and refine analysis by location of media creation.
  • Overlay location of proposed matches onto maps.
  • Chart movements of individuals of interest by location and time of sightings.
  • Link individuals at the same location and time even if they do not appear together in media.

3.3  Architecture and Integration with Existing Systems

In addition to utilising COTS components, open standards and cloud-computing architecture to enable massive scalability, a well delineated scope of functionality and open API enables:

  • Flexibility in customisation and integration with existing systems and workflows.
  • Well-defined mechanisms of loading data and automating ingestion of media.
  • Dynamic alteration and sharing of watchlists, media, system-generated results and operator analysis.

3.4  Hosting, Cloud and Virtualisation Options

Full architectural flexibility enables flexibility of hosting options. Organisations can elect to:

  • Take advantage of IaaS and SaaS options on public sector hosting offerings.
  • Fully self-host the solution on private and secure premises and datacentres.
  • Deploy in a hybrid manner.

Indeed, managed AWS or Azure offerings can be utilised to bulk process media, utilising non-return gateways to propagate identified sensitive data to more secure facilities.

3.5  Working Hand-in-Glove with Trained Forensic Investigators

Humans will always remain the critical and essential part of intelligence analysis; such solutions do not replace the intricate skills and knowledge of trained investigators. Rather, the operator is enabled to intelligently direct and apply their training at suggested results, eliminating the necessity of rote viewing of countless hours of media either in a sequential our random fashion.

Integration of enhanced verification, charting and mapping tools enables operators to conduct detailed analysis of suggested matches and identifications.

 

4 Potential Use Cases

There are multiple applications of a solution as described herein within military, law enforcement, intelligence and public-site security agencies. These are summarised into four broad categories:

4.1  Time Critical Investigations, Media of Critical Importance

Often, authorities need to quickly process evidence to identify and apprehend individuals. The scale of the investigation can be huge and the amount of media that needs to be processed massive.

The media acquired in these instances can be of such critical importance that the authorities may choose to review it all in its entirety. However, immediate and decisive action is critical. Rather than sifting through the media in a random or sequential fashion, a media analysis solution can quickly direct the investigators to portions of the media that are most likely to deliver immediate results. Full review of the media can be conducted afterwards.

4.2  Bulk Ingestion of Media Arising from Criminal Investigations

During routine operations or investigations, authorities may recover significant quantities of media from multiple sources that need to be processed to further the investigation or to assist in building an evidence base for prosecution. Examples include:

  • Military or counter-terror officers raiding terrorist facilities.
  • Specialist organised crime investigators raiding organised crime offices.
  • Child protection officers raiding premises of individuals or organisations involved in child exploitation.

Automating processing provides investigating officers an overall summary of the contents including focus areas for further investigation.

4.3  Continuous Background Processing of Media Sources

Authorities may as a matter of routine have access to masses of media which may contain actionable intelligence, but typically would never be viewed or processed due to a lack of resource. Intelligence in this media may be missed entirely and never acted upon.

This media can now be bulk ingested and processed in an automated fashion to flag relevant intelligence, using operator controlled criteria, to the authorities as required for follow-up processing.

  • Routine and automated processing of accessible media can flag actionable intelligence that may help disrupt future attacks.

4.4  Near Real-Time Watchlist Checking from Live Surveillance Cameras

By integrating any number of remote surveillance cameras to such a centralised matching platform eliminates the need to install and maintain costly local software and hardware to perform local face matching as well as the need to store potentially secure watchlist data locally at the camera locations. The problems associated with live streaming of HD media over low bandwidth network connections is resolved through the application of local face-detection and cropping; only small image files of cropped faces need be sent to the central data centre over encrypted channels.

4.4.1        Centralised Archive of “Seen Faces”

In addition to submitting search probes to the server for searching against one or more watchlists, search probes can be enrolled in a “seen faces” archive which can be interactively or automatically searched (using face recognition) by investigators or when submitting videos for processing.

 

5 A Compelling Business Case

The solution can be made available using a compelling SaaS model. The open and standard nature of the solution ensures it can run in existing on-premise datacentres or outsourced to secure hosting partners.

Whilst the human operator is an essential part of intelligence analysis, an entry-level system empowers the analyst to process up to an order-of-magnitude more media on a daily basis. This enables trained operators to apply their expertise in a more focussed manner than manually watching hour upon hour of media.

Efficiency is dramatically boosted by bulk processing media 24×7 at a constant and predictable level of focus and accuracy: operational staff can focus on analysing results.

 

6 Summary

Security concerns are increasing whilst budgets are limited. The focussed application of technology can improve efficiency and aid law enforcement agencies to rise to this challenge.  The massive increase in the creation of digital media and the availability of cheap computing provides authorities with the ability to bulk ingest and process media in an automated fashion. Results are continuous and predictable. Trained analysts can now focus their skills on investigating suggested results and on intelligence extracted by automated systems. Not only does this provide the ability to process critical media even faster than ever before to respond to time critical investigations, but it also enables authorities to extract intelligence from media sources that in the past may never even have been looked at because of the significant resource this previously would have entailed. The same centralised platform can also be used to search in near real-time faces from any number of remote cameras against centralised watchlists of individuals of interest.


On the BBC Newsnight Report on Terrorism and Face Recognition

Richard Watson’s report on the 20th July edition of BBC Newsnight on the threat of terrorism and and the potential use of face recognition to combat it was informative, balanced and effectively presented the scale of the challenges faced, as well as the challenges in any potential use of the technology.

It’s important to realise that face recognition is not a panacea. But it is an effective tool that can drastically improve the efficiency of our intelligence and police agencies.

 

The figure cited of 40 officers to trail one suspect full time over 20 hours is not off the mark. Ex Chief Constable of the British Transport Police Andrew Trotter neatly summed it when he said “It is a huge labour intensive. Huge, and these people may do nothing for months, years. … And all the time there might be others that needed more attention. That diverts resources from other things…”.

Products such as the one demonstrated by Zak Doffman of Digital Barriers present an excellent example of technology available and typical and effective uses of them. However, Roger Cumming hit the nail on the head when he said “If an alarm is rung through your camera system picking up one of these people, what do you actually do? Because at that state all you’ve got is a positive identification of somebody on a watchlist? Do they represent a threat? Are the planning some sort of attack? Or are they just going about their business?…”.

The use of the technology in itself will pose new challenges.

The demonstrated solution is just one of many that can effectively perform live watchlist alerting on surveillance cameras to positive effect. But I don’t believe this use of face recognition alone represents the greatest benefit to police, and may not sufficiently improve efficiency to warrant the cost and generate a return on the investment.

It is likely that after each of the terrorists attacks in recent months, there was a substantial quantity of video evidence that needed to be manually reviewed at great use of resource. A significant challenge faced by police is the effective and efficient extraction and linking of intelligence from all of this media which can come from multiple sources, including CCTV, body worn video, members of the public, the Internet, the dark Web, news broadcasts and digital forensics (confiscated computers, phones, drives etc).

This represents a phenomenal Big Data challenge which is becoming increasingly solvable with the increasing availability of on-demand and elastic cloud computing paradigms. If we can rapidly process this media (at much greater speed than real time) and extract assets using face recognition and other detection technologies for presentation to reviewing investigators, this will significantly reduce the amount of time they need to laboriously watch it themselves, whilst increasing the intelligence they obtain from it, enabling them to rapidly “connect the dots”.

More actionable and linked intelligence, obtained quicker and cheaper. This can feed the watchlists the live surveillance cameras are searching in an integrated fashion off the same platform.

And perhaps just as importantly, introduce efficiency to feed a business case to help ensure the technology can be feasibly adopted.

You can watch the programme here: http://www.bbc.co.uk/programmes/b006mk25


Allevate Announces Continued Availability of MXSERVER on UK Crown Commercial Service Digital Marketplace (G-Cloud)

newsreleasePowerful Cloud-Enabled Video and Photographic Forensic Analysis System Incorporating Face Recognition is available to all UK government, intelligence and law-enforcement agencies to assist in combatting crime and terrorist activities. MXSERVER automates the bulk-processing of media for forensic analysis and is already proven by US Federal agencies to provide an “Order of Magnitude” efficiency gain and significantly enhanced identification of suspects.

LONDON, UK 23 May 2017:  Allevate today announces the continued availability of MXSERVER on the UK Crown Commercial Service’s Digital Marketplace G-Cloud 9 Framework.  Allevate’s SaaS G-Cloud offering is enabled by Sungard Availability Services, who provides a Secure Managed Cloud IaaS and PaaS platform, with OFFICIAL classification, for UK Government Service Provision.

The below is extracted from our announcement of availability on G-Cloud 8.

Our security services are faced with a relentless increase in digital media — from CCTV and surveillance cameras, police body worn video, online sources such as Facebook and YouTube, confiscated phones and computers and, increasingly, ‘crowd-sourced’ from members of the public. There has been no easy and cost-effective way to access the intelligence this media contains. Experienced and expensive human capital has been assigned the rote task of watching countless hours of video in the hope of finding useful information.

MXSERVER, from Tygart Technology, processes vast amounts of textual, video and photo collections quickly – automatically discovering, grouping and extracting segments depicting people. Using face recognition technology, this solution searches media archives to find other assets which depict individuals of interest. It also indexes the digital media to enable it to be efficiently searched using a photograph of a face, previewed and analysed via an intuitive web-based user interface. Results become available in minutes rather than hours or days because the digital media files are processed in parallel over a distributed cloud-architecture.

Allevate emphasizes that “MXSERVER delivers a Big Data solution for law-enforcement’s growing video and photo assets. It provides a significantly enhanced identification capability that is quicker and more efficient than manually watching video. “

From today, access to both the software and all hosting and storage services are available on Digital Services Marketplace G-Cloud 8 framework using an easy to calculate monthly service fee. The G-Cloud catalogue is open to all public sector clients and is designed to provide a simple streamlined process for buying ICT focused products and services as a commodity without having to invite tenders from suppliers.

About Allevate Limited

Founded in London in 2007, Allevate works with law enforcement, intelligence and government agencies to enhance public safety by ensuring positive identification through the application of biometric and identification technology.

  • Ensure Positive IdentificationCrown-Commercial-Service-Supplier_logo
  • Enhance Public Safety
  • Reduce Operational Costs

Visit us at http://allevate.com , email us at contact@allevate.com, call us on +44 20 3239 6399 and follow us at @Allevate.

About the UK Crown Commercial Service

The UK Crown Commercial Service (CCS) works with both departments and organisations across the whole of the public sector to ensure maximum value is extracted from every commercial relationship and improve the quality of service delivery. The CCS goal is to become the “go-to” place for expert commercial and procurement services.


Combatting Crime and Protecting Crowded Places. Face Recognition in the Cloud Demonstrated at UK Security Expo 2016 in London.

 

newsreleaseAllevate’s Cloud-hosted Face-Searcher face recognition service integrated with Facewatch’s digital crime reporting system to feature in UK Security Expo’s Securing Crowded Places Immersive Demonstrator. Nationally available in Brazil, UK launch imminent.

 

LONDON, UK 25th November 2016: Allevate and Facewatch today announce that Allevate’s Face-Searcher, a cloud-hosted face recognition service integrated with Facewatch’s online crime reporting system, will feature in the Securing Crowed Places Immersive Demonstrator at the UK Security Expo on the 30th November and 1st December 2016 at Olympia, London. After its successful Brazilian launch, the integrated offering is now due for imminent launch in the UK.

The Immersive Demonstrator at UK Security Expo 2016 will be under the theme of ‘Securing Crowded Places’ and is being run in association with The Home Office JSaRC, the Centre for the Protection of National Infrastructure (CPNI) and other relevant Government Departments.

Allevate’s Face-Searcher service enables organisations to utilise facial recognition as a hosted cloud service. It requires minimal capital outlay, incorporates advanced, world-class face recognition technology and eliminates the need to install or maintain a complicated software infrastructure or related compute platform on clients’ premises.

Facewatch enables organisations to report crimes online and submit moving and still CCTV images as evidence to the police, as well as share this imagery between businesses in related subscribed groups (in compliance with Data Protection guidelines) to reduce crime.

Following an imminent UK launch, UK Facewatch subscribers will be able to instantly and automatically share their images of Subjects of Interest to Face-Searcher’s watchlists, thereby allowing real-time watchlist alerting to any device connected to Facewatch’s integrated alert management system. This integrated offering will help businesses prevent crime by warning them if someone entering their premises is on a watchlist of known offenders.

Face-Searcher is built on the industry-proven enterprise-grade MXSERVERTM platform enabling automated facial detection and recognition, developed by Tygart Technology, Inc.

Additionally, Allevate will be providing a live demonstration of the MXSERVERTM platform in the Technology Workshops and Live Demonstrations in the conference stream of the exhibition, entitled “Beyond Live Surveillance: The Application of Face Recognition to Improve Forensic Analysis of Masses of Digital Media“, Day 2, 1st December, 2016 at 1240pm.

MXSERVERTM is also available on the UK’s Crown Commercial Service Digital Marketplace G-Cloud 8 Framework and is Powered by Sungard Availability Services.

Find out more on stand A41 at the exposition, in collaboration with Sungard Availability Services.


About Allevate Limited

Founded in London in 2007, Allevate works with law enforcement, intelligence and government agencies to enhance public safety by ensuring positive identification through the application of biometric and identification technology.

  • Ensure Positive Identification
  • Enhance Public Safety
  • Reduce Operational Costs

Visit us at http://allevate.com, email us at contact@allevate.com, call us on +44 20 3239 6399 and follow us at @Allevate.

About Facewatch

Founded in London in 2010, Facewatch has worked with UK policing to create the world’s first private sector crime reporting platform that enables business and police to share information securely and instantly.

Visit us at http://www.facewatch.co.uk, email us at info@facewatch.co.uk, call us on +44 20 7930 3225 and follow us at @Facewatch.

About Tygart Technology, Inc.

Tygart Technology, Inc. is a leading provider of enterprise-grade video and photographic analysis and biometric recognition systems. Tygart provides the U.S. Military, Intelligence Community and Law Enforcement markets with innovative software solutions that manage and automate the processing of massive volumes of digital video and photograph collections.

Visit us at http://www.tygart.com or call 1-304-363-6855.


Allevate Seeking Global Distributors and Agents for Face-Searcher Service

Allevate is actively seeking global distributors and agents for its new cloud-hosted Face-Searcher Service integrated with Facewatch’s secure online crime reporting service. The integrated offering enables businesses, public and police to tackle low-level crime by sharing images within groups and then utilise cloud-hosted face recognition to raise alerts back to the business.

Key Benefits:

  • No complicated software to install or maintain.
  • Enables businesses to collaborate with each other and the police by sharing imagery.
  • Integrated with the industry’s best biometric algorithms.
  • Affordable monthly service fee with no or minimal up-front capital expenditure.

 

Already launched in Brazil, the integrated service is available globally and we are now seeking both:

  • Leading security and surveillance organisations to act as a distribution channel.
  • Agents to manage and on-board distributors within specific geographic territories.

The Value to You

Our integrated offering supplies our distribution channel with an affordable, SaaS structured offering to augment your already successful and credible security and surveillance operation with a cloud-hosted and easy to maintain facial recognition service.

Coupled with your extensive experience in CCTV installation and configuration and control room and monitoring services, it adds further value that enables your customers to collaborate with each other and the police and to further enhance the security of their premises with face recognition.

 

If you are interested or to find out more, please do not hesitate to contact us here.

Download a datasheet on Face-Searcher here.

 

 

 


Allevate’s Face-Searcher in Action: Cloud-Enabled Face Recognition

A test-run of Allevate’s Face-Searcher service integrated with the online Facewatch crime reporting system:

  • A camera with a lightweight laptop in the UK
    • Detecting and cropping faces from the video stream
  • Submitting image files of cropped faces for ultra-scalable and accurate face matching in the Cloud in Amazon Web Services in USA.

… with

  • Watchlist data syncronised with a Facewatch test instance in Amazon Web Services in Brazil

… reporting

  • Alerts to the Facewatch test subscriber back in the UK, all in under 3 seconds from sighting of suspect.

Why?

  • Because we can, and to demonstrate the flexibility of our cloud-based matching system.

 

Available now in Brazil., hosted locally in Brazil.

Coming soon elsewhere.

 

Download the Face-Searcher datasheet here.

 

Face-Searcher with Facewatch


Cloud Face Recognition Integrated with Secure Online Crime Reporting Launched in Brasil

 

newsreleaseAllevate’s Cloud-Hosted Face-Searcher Face Recognition Service integrated with the Facewatch secure online crime reporting system is launched in Brasil. This integrated offering, to all organisations large or small, enables the provision of face recognition in the cloud, matching against data-sets created from real-time crime reporting.  

LONDON, UK and Rio de Janeiro, Brasil 17 August 2016:  Allevate today announces the launch of its Face-Searcher service, enabling organisations, large or small, to utilise facial recognition as a hosted cloud service. Additionally, Facewatch, the secure online crime reporting system, announces immediate availability of an integrated Facewatch and Face-Searcher offering, launching initially in Brasil.

Facewatch enables organisations to report crimes online and submit moving and still CCTV images as evidence to the police, as well as share this imagery between businesses in related subscribed groups (in compliance with Data Protection guidelines) to reduce crime.

Allevate’s Face-Searcher service enables organisations to utilise facial recognition as a hosted cloud service. It requires minimal capital outlay, incorporates advanced, world-class face recognition technology and eliminates the need to install or maintain a complicated software infrastructure or related compute platform on your premises. The Face-Searcher Edge component detects and crops faces from retailyour CCTV cameras and submits them to the cloud-service for matching.

Facewatch subscribers can now instantly and automatically share their images of Subjects of Interest to Face-Searcher’s watchlists, thereby allowing real-time watchlist alerting to any device connected to Facewatch’s integrated alert management system. This integrated offering can now help businesses prevent crime by warning them if someone who enters their premises is on a watchlist of known offenders.

Simon Gordon, of Facewatch, says “A major factor that has hindered the wide-scale adoption of face recognition by business has been the requirement to install and manage costly and complex software. Allevate’s cloud-hosted SaaS offering removes this headache and enables businesses to benefit from the accuracy of the industry’s best face recognition algorithms in a cloud-enabled shared-services environment with a simple easy to understand monthly subscription fee.”

Carl Gohringer, of Allevate, continues “The best face-recognition technology in the world is useless unless businesses have accurate and reliable subject matter to match against. Facewatch has already proven invaluable in enabling businesses to seamlessly interact with their local police. Now, they can co-operate by sharing this same imagery amongst their local business groups.”

Face-Searcher is built on the industry-proven enterprise-grade MXSERVERTM platform enabling automated facial detection and recognition, developed by Tygart Technology, Inc. MXSERVERTM is the only biometric search engine on the market designed to handle Big Data (processing massive amounts of photos and videos) by leveraging a cloud-based architecture for faster parallel processing of services.  MXSERVERTM is proven and utilised by Defence, Intelligence and Law Enforcement organisations and has also been used to enhance security at major events, such as the 2015 European Games, a major international sporting event.

This integrated offering is being made available in Brasil by our local partner, Staff Security Ltd. Humberto Bambira, of Staff Security, says “We have been developing this exciting opportunity for the mass market rollout of facial recognition in Brasil with Facewatch for two years and I am delighted to see the launch of the service.”


About Allevate Limited

Founded in London in 2007, Allevate works with law enforcement, intelligence and government agencies to enhance public safety by ensuring positive identification through the application of biometric and identification technology.

  • Ensure Positive Identification
  • Enhance Public Safety
  • Reduce Operational Costs

Visit us at http://allevate.com , email us at contact@allevate.com, call us on +44 20 3239 6399 and follow us at @Allevate.

 

About Facewatch

Founded in London in 2010, Facewatch has worked with UK policing to create the world’s first private sector crime reporting platform that enables business and police to share information securely and instantly.

Visit us at http://www.facewatch.co.uk,  email us at info@facewatch.co.uk, call us on +44 20 7930 3225 and follow us at @Facewatch.

 

About Tygart Technology, Inc.

Tygart Technology, Inc. is a leading provider of enterprise-grade video and photographic analysis and biometric recognition systems.  Tygart provides the U.S. Military, Intelligence Community and Law Enforcement markets with innovative software solutions that manage and automate the processing of massive volumes of digital video and photograph collections.

Visit us at www.tygart.com or call 1-304-363-6855.

 


Allevate Announces Availability of SaaS Face Recognition Service on UK’s Digital Marketplace (G-Cloud 8)

newsreleasePowerful Cloud-Enabled Video and Photographic Forensic Analysis System Incorporating Face Recognition is available to all UK government, intelligence and law-enforcement agencies to assist in combatting crime and terrorist activities. MXSERVER, enabled by Sungard Availability Services, automates the bulk-processing of media for forensic analysis and is already proven by US Federal agencies to provide an “Order of Magnitude” efficiency gain and significantly enhanced identification of suspects.

LONDON, UK 02 August 2016:  Allevate today announces that MXSERVER is available on the UK Crown Commercial Service’s Digital Marketplace G-Cloud 8 Framework.  Allevate’s SaaS G-Cloud offering is enabled by Sungard Availability Services, who provides a Secure Managed Cloud IaaS and PaaS platform, with OFFICIAL classification, for UK Government Service Provision.

Our security services are faced with a relentless increase in digital media — from CCTV and surveillance cameras, police body worn video, online sources such as Facebook and YouTube, confiscated phones and computers and, increasingly, ‘crowd-sourced’ from members of the public. There has been no easy and cost-effective way to access the intelligence this media contains. Experienced and expensive human capital has been assigned the rote task of watching countless hours of video in the hope of finding useful information.

MXSERVER, from Tygart Technology, processes vast amounts of textual, video and photo collections quickly – automatically discovering, grouping and extracting segments depicting people. Using face recognition technology, this solution searches media archives to find other assets which depict individuals of interest. It also indexes the digital media to enable it to be efficiently searched using a photograph of a face, previewed and analysed via an intuitive web-based user interface. Results become available in minutes rather than hours or days because the digital media files are processed in parallel over a distributed cloud-architecture.

Allevate emphasizes that “MXSERVER delivers a Big Data solution for law-enforcement’s growing video and photo assets. It provides a significantly enhanced identification capability that is quicker and more efficient than manually watching video. “

From today, access to both the software and all hosting and storage services are available on Digital Services Marketplace G-Cloud 8 framework using an easy to calculate monthly service fee. The G-Cloud catalogue is open to all public sector clients and is designed to provide a simple streamlined process for buying ICT focused products and services as a commodity without having to invite tenders from suppliers.

About Allevate Limited

Founded in London in 2007, Allevate works with law enforcement, intelligence and government agencies to enhance public safety by ensuring positive identification through the application of biometric and identification technology.

  • Ensure Positive IdentificationCrown-Commercial-Service-Supplier_logo
  • Enhance Public Safety
  • Reduce Operational Costs

Visit us at http://allevate.com , email us at contact@allevate.com, call us on +44 20 3239 6399 and follow us at @Allevate.

About the UK Crown Commercial Service

The UK Crown Commercial Service (CCS) works with both departments and organisations across the whole of the public sector to ensure maximum value is extracted from every commercial relationship and improve the quality of service delivery. The CCS goal is to become the “go-to” place for expert commercial and procurement services.


“Facial recognition system was used on live video from surveillance cameras at the 2015 European Games, in Baku, Azerbaijan”

From nextgov.com US SPIES TRAIN COMPUTERS TO SPOT SUSPICIOUS ACTIVITY IN LIVE VIDEOS

“Last year, a facial recognition system was used on live video from surveillance cameras at the European Games, in Baku, Azerbaijan, according to the tool’s developer, Tygart. During the June 2015 event, organizers watched a webpage that could issue an alert if a face in the crowd matched that of an individual on a watch list. ”

Baku2015 was the inaugural European Olympic Committee’s First European Games and was attended by 6,000 athletes from over 50 countries over 16 days, with over 600,000 tickets sold.

MXSERVER is a highly scalable cloud-enabled solution to process videos and photographs applying face recognition.

All faces in the media are:

  • Extracted and cropped
  • Searched against a watchlist
  • Indexed so the media can be searched with a photograph

Media inputs to MXSERVER include:

  • Body Worn Video
  • Live surveillance cameras (CCTV)
  • Archived video
  • Online Sources (YouTube, Facebook etc)
  • Confiscated hardrives, phones, PCs (Digital Forensics)

You can view more info on MXSERVER at:
http://allevate.com/index.php/mxserver/mxserver_presentation/

… and read more about the proposition at:
http://allevate.com/index.php/2013/08/01/intelligence-and-efficiency-through-on-demand-media-analysis-using-face-recognition/


Allevate Now Offering Toshiba’s Face Recognition Integrated with the MXSERVER Cloud-Enabled Media Analysis Platform

newsrelease

Integrated Offering Combines MXSERVER’s Proven Ability to Massively Scale the Processing of Vast Quantities of Video and Photographs with the NIST Demonstrated Accuracy of Toshiba’s Face Recognition Library

 

 

 

London, UK — 15 March 2016Allevate Limited today announced that, working cooperatively with Tygart Technology, it is now offering Toshiba’s Face Recognition Software Library as an integrated component of Tygart’s MXSERVER™ to enable European government, law enforcement and security agencies to further enhance public safety. MXSERVER is an algorithm-agnostic, cloud-enabled system that processes vast quantities of video and photo collections to transform these digital assets into searchable resources by using face recognition.

According to Allevate, one of the key strengths of Tygart’s MXSERVER is the fact that it is agnostic to and can be deployed with multiple commercially available face recognition algorithms (COTS) or government developed face recognition algorithms (GOTS). This enables Allevate to work co-operatively with the end-user and algorithm vendors to determine the most appropriate selection of algorithm to meet each client’s unique needs. Additionally, clients have the flexibility to continually improve performance by using the best available algorithm over the life of the project as requirements change. Traditionally, having purchased an entire turn-key platform from a specific face recognition algorithm vendor, clients would have to sacrifice their entire investment in that vendor’s platform should they wish to change the underlying algorithms for any reason. MXSERVER enables clients to leverage their investment in a scalable Enterprise Grade technology platform by only changing the underlying algorithm components.

Toshiba’s Face Recognition Software Library is a Software Development Kit (SDK) that provides automated face detection and tracking in videos and photos, face recognition matching and photograph quality assessment.  The combination of this SDK with MXSERVER will provide government, law enforcement and security agencies with enhanced surveillance, monitoring and forensic analysis capabilities.

An Allevate spokesman said “Toshiba is one of the leading providers of face recognition technology and continues to be one of the top performers as demonstrated by independent testing by the US National Institute of Standards and Technology (NIST)”. He continued “We are very pleased to offer our clients further flexibility with the provision of Tygart’s MXSERVER with a Toshiba-inside option.”

“We are very proud of the accuracy and price performance ratio of Toshiba’s enterprise-grade software algorithms, based on the result of FRV2013 by NIST,” said Nobuyoshi Enomoto, Deputy Senior Manager of Toshiba. “Integration with the MXSERVER cloud-enabled platform strengthens our offering with a scalable search and index capability to support real-time surveillance and monitoring for public security and post-event forensic analysis.” He continues “We are pleased to be working with Allevate to make this joint offering available to Europe’s law-enforcement, intelligence and security agencies.”

—ENDS—

About MXSERVER

MXSERVER is a cloud-architected face recognition system that processes vast quantities of video and photo collections extracted from police body cameras, online sources, surveillance systems, digital forensics and, increasingly, “crowd-sourced” from the public.

MXSERVER can transform these digital assets into searchable resources. Using face recognition technology it searches media archives to find individuals of interest. It also indexes the media to enable it to be searched using a photograph. Trained investigators are freed to intelligently apply their skills without having to view countless hours of media.

 About Allevate Limited

Visit us at http://allevate.com, email us at contact@allevate.com, call us on +44 20 3239 6399.

About Toshiba Corporation

For more information, visit http://www.toshiba.co.jp/sis/en/scd/face/face.htm


Find People Fast in Media using Cloud-Based Face Recognition during Forensic Analysis

When tragic events or social disorder occur, forensic investigators have a long and daunting task of reviewing countless hours of CCTV footage. Increasingly, especially at public events attended by large numbers of people carrying mobile phones with HD cameras, authorities rely on  members of the public to turn in photographs and videos they have taken in the hope that they will contain useful intelligence. Much of this media is already uploaded to public sites such as Facebook and YouTube, providing another rich source of information.

Additionally, police have to review countless hours of media obtained from confiscated computer hard drives, mobile phones and portable cameras and flash memory devices.

Face Recognition?

All of this creates a significant resource burden;  this footage must be watched by people. The application of face recognition technology can play a crucial role in identifying potential suspects.

An Automated Media Processing Cloud

A solution to automate the processing of this staggering amount of media to quickly and efficiently unlock actionable intelligence is required to save significant time and human capital. The ability to automate this would allow the more efficient application of resources as well as massively speed up time-critical investigations.

However, the need goes far beyond the simple application of face recognition technology.

What is needed is a server-based system that can process vast amounts of media quickly to transform files from  mobile phones, flash memory devices, online sources, confiscated computers and hardrives and video surveillance systems into searchable resources. This would enable forensic investigators to work more efficiently and effectively by automatically finding, extracting and matching faces from very large collections of media to discover, document and disseminate information in  real-time.

Such a powerful video and photograph processing architecture should automatically ingest, process, analyse and index hundreds of thousands of photographs and videos in a centralised repository to  glean associations in a cloud environment. Instrumental would be the ability to:

  • Automatically find, extract and index faces to enable  the biometric and biographic searching of media.
  • Create and manage watchlists of people of interest via a web-based interface.
  • Find all instances of photos and videos where a person of interest has been seen.
  • Quickly review and process  media to identify, locate, and track persons of interest, their associates and their activities.
  • Discover, document and diagramtically view  associations between people of interest, their activities and networks.
  • Use media meta-data to geotag video footage and watchlist hits and overlay and present on maps.

Public Facing Cloud-Service to Crowd-Source Media

Finally, a public-facing interface to such a system would enable members of the public to upload their media in a self-service manner to enable quick and ready access by the authorities to this raw data for automatic processing.

Enhance Public Safety and Reduce Budgets

Read about how MXSERVER addresses the AMAIS space (Automated Media Analysis for Intelligence Searching)

This solution is now available to UK public sector on the Government Procurement Service CloudStore – G-Cloud iii Framework as a commodity from the catalogue without having to invite tenders from suppliers.

 


Could Automating Media Processing Aid the Forensic Investigation into the Boston Marathon Bombing?

The horror of the events at the marathon in Boston 2 days ago is still very raw. People are united in their sympathy for the victims and their families, their revulsion of these despicable acts and their solidarity in not succumbing to terror. The FBI vows to “…go to the ends of the Earth to find the bomber” with President Obama openly stating the “…heinous and cowardly…” event to be “…and act of terror”.

The investigation into the bombing is in its nascent phases, with the Boston Police Commissioner Ed Davis admitting that they are dealing with the “…most complex crime scene that we have dealt with in the history of our department.” Still, authorities are already honing in on crucial evidence and beginning to release details; BBC news reports that a source close to the investigation told AP news agency that the bombs consisted of explosives placed in 1.6-gallon pressure cookers, one with shards of metal and ball bearings, the other with nails, and placed in black bags that were left on the ground. Images of what appear to be a trigger mechanism have already been released.

Face Recognition?

Forensic investigators have a long and daunting task ahead of them with countless hours of CCTV footage to  pore over, and some people are already suggesting that the application of face recognition technology can play a crucial role in identifying potential suspects. However CCTV footage, especially from older systems that have not been specifically configured for the task, is notoriously unreliable as a source for face recognition.

Perhaps more useful at an event attended by so many, most of whom will have been carrying and using mobile phones and cameras, is the footage acquired by members of the public. Images and video captured by these high-quality devices will potentially be of much greater use than CCTV and authorities have appealed for people to turn in photographs and videos they have taken in the hope that they will contain useful intelligence. Much of this media will already have been uploaded to public sites such as Facebook and YouTube.

 An Automated Media Processing Cloud

A solution to automate the processing of this staggering amount of media to quickly and efficiently unlock actionable intelligence is required to save significant time and human capital. The ability to automate this would allow the more efficient application of resources as well as massively speed up a time-critical investigation.

However, the need goes far beyond the simple application of face recognition technology.

What is needed is a server-based system that can process vast amounts of media quickly to transform files from  mobile phones, flash memory devices, online sources, confiscated computers and hardrives and video surveillance systems into searchable resources. This would enable forensic investigators to work more efficiently and effectively by automatically finding, extracting and matching faces from very large collections of media to discover, document and disseminate information in  real-time.

Such a powerful video and photograph processing architecture should automatically ingest, process, analyse and index hundreds of thousands of photographs and videos in a centralised repository to  glean associations in a cloud environment. Instrumental would be the ability to:

  • Automatically find, extract and index faces to enable  the biometric and biographic searching of media.
  • Create and manage watchlists of people of interest via a web-based interface.
  • Find all instances of photos and videos where a person of interest has been seen.
  • Quickly review and process  media to identify, locate, and track persons of interest, their associates and their activities.
  • Discover, document and view  associations between people of interest, their activities and networks.

Finally, a public-facing interface to such a system would enable members of the public to upload their media in a self-service manner to enable quick and ready access by the authorities to this raw data for automatic processing.

 


Biometrics 2011: Panel Biometric Matching as a Software Service (SaaS)

I’m looking forward to the Biometrics2011 conference in London next week.

One of the more interesting presentations is the Biometrics and Identity Matching as a Software Service panel discussion at the end of the last day.

In my view, this is a topic that is ripe for discussion, given the current levels of indebtedness of our governments.

With the current wave of austerity sweeping the world’s nations at the moment, most programmes entailing large capital expenditure are out, unless they demonstrate significant return on investment in the same fiscal year; large government IT projects take years to re-coup investment.

Suppliers are looking at recovering this loss of business by self-financing other business models, and one that is becoming increasingly popular is selling transactional services. Basically this entails moving the up-front investment from the customer to the supplier, as well as the onus to realise the ROI over the life of the programme.

Such models are increasingly supported by trends such as cloud computing, data center consolidation, shared infrastructure and virtualisation.

In today’s economic climate, the ability to move an initial large up-front capital expenditure to a long-term annual operating expenditure spread over the life of the programme is understandably attractive to customers.

On the flip-side, these same economic conditions will make it more difficult for suppliers to structure such deals, and they will remain the preserve of the larger suppliers with pockets deep enough to weather the current economic storm.

That this business model is attractive to larger government biometric identity programmes is no surprise.

In fact, this arrangement is nothing new. The Western Identification Network (WIN) is a collaboration of eight US states, and is one of the larger criminal / law enforcement AFIS systems in existence. It is hosted, run and owned by the supplier, with the states paying for match services.

The UK’s Ident1 Criminal AFIS system is structured in a similar manner.

Interestingly, the panel members of the Biometrics 2011 panel discussion represent NEC (suppliers of the US WIN system), Northrop Grumman Corporation (suppliers of the UK Ident1 system), and the UK National Police Improvement Agency (customers for the UK Ident1 system), so they should know what they are talking about!