Crime-fighting Tool Identifies Suspicious Individuals at Crime Scenes

It's become a standard plot device of television detective shows: criminals returning to the scene of the crime. And law enforcement officials believe that perpetrators of certain crimes, most notably arson, do indeed have an inclination to witness their handiwork. Also, U.S. military in the Middle East feel that IED bomb makers return to see the results of their work in order to evolve their designs.

Now a team of University of Notre Dame biometrics experts are developing a crime-fighting tool that can help law enforcement officials identify suspicious individuals at crime scenes.

Kevin Bowyer and Patrick Flynn of Notre Dame's Computer Science and Engineering Department have been researching the feasibility of image-based biometrics since 2001, including first-of-their-kind comparisons of face photographs, face thermograms, 3-D face images, iris images, videos of human gait, and even ear and hand shapes.

While attending a meeting in Washington, D.C, Bowyer listened as military and national security experts discussed the need for a tool to help identify IED bombers in the Middle East.

He decided to join forces with Flynn and Jeremiah Barr, a doctoral student in computer science and engineering, to tackle the challenge he heard expressed at the Washington meeting. The researchers developed a "Questionable Observer Detector (QuOD)" to identify individuals who repeatedly appear in video taken of bystanders at crime scenes.

The challenge was especially daunting because the researchers lacked a data base to compare faces against. Also, many times crime scene videos are shot by witnesses using handheld videos and are often of poor quality. Additionally, many criminals try to disguise their appearance in various ways.

In response, the Notre Dame team focused on an automatic facial recognition tool that didn't need to match people against an existing database of known identities. Instead, Bowyer, Flynn and Barr create "face tracks" for all individuals appearing in a video and repeat the process for all available video clips. The face tracks are compared to determine if any faces from different video clips look similar enough to match each other. When the technology spots a match, it adds it to a group of video appearances featuring just that person. In this way, it attempts to cluster together the pieces of different video clips that represent the same person.

An individual is considered suspicious if he or she appears too frequently in the set of videos. The "too many" number is determined by law enforcement officials based on the number of crimes and videos available.

Although the technology shows great promise, Bowyer, Flynn and Barr admit they still have serious technical challenges they are working to overcome. Optimum facial recognition technology requires high quality lighting and video resolution, which is often unavailable at crime scenes. Also, people may not be looking directly at the camera in video of crowds of bystanders. And the identification of a questionable observer becomes more computationally demanding in cases where there a large number of videos to be analyzed.

The researchers are confident, however, that these challenges can be overcome and are continuing to work to improve their system. They are also confident that civil liberties concerns are minimized and positive social benefit is invovled, given that the tool helps officials identify individuals by their actual presence at multiple crime scenes rather than by suspicion.

Featured

  • Allegion, Comfort Technologies Implement Mobile Credentials at the Artisan Apartment Homes in Florida

    Artisan Apartment Homes, a luxury apartment complex in Dunedin, Florida, recently transitioned from mechanical keys to electronic locks and centralized system software with support from Allegion US, a leading provider of security solutions, technology and services, and Florida-based Comfort Technologies, which specializes in deploying multifamily access control, IoT devices and software management solutions. Read Now

  • Mall of America Deploys AI-Powered Analytics to Enhance Parking Intelligence

    Mall of America®, the largest shopping and entertainment complex in North America, announced an expansion of its ongoing partnership with Axis Communications to deploy cutting-edge car-counting video analytics across more than a dozen locations. With this expansion, Mall of America (MOA) has boosted operational efficiency, improved safety and security, and enabled more informed decision-making around employee scheduling and streamlining transportation for large events. Read Now

  • Security Industry Association Launches New “askSIA” AI Tool

    The Security Industry Association (SIA) has unveiled a brand-new SIA member benefit – askSIA, a conversational AI agent designed to help users get the most out of their SIA membership, easily access SIA resources and find the latest information on SIA’s training and courses, reports and publications, events, certification offerings and more. SIA members can easily find askSIA by visiting the SIA homepage or looking for the askSIA icon in the top left of webpages. Read Now

    • Industry Events
  • Industry Embraces Mobile Access, Biometrics and AI

    A combination of evolving workplace dynamics, technology innovation and new user expectations is changing how people enter and interact with physical spaces. Access control is at the heart of these changes. Combined with biometrics and AI, mobile access control has become increasingly crucial for deploying entry solutions that are seamless, secure and adaptive to user needs. Read Now

  • Sustainable Video Solution Delivered for Landmark City of London Office Development

    An advanced, end-to-end video solution from IDIS, with a focus on reducing waste and costs, has helped a major office development in the City of London align its security with sustainability objectives. Read Now

New Products

  • Automatic Systems V07

    Automatic Systems V07

    Automatic Systems, an industry-leading manufacturer of pedestrian and vehicle secure entrance control access systems, is pleased to announce the release of its groundbreaking V07 software. The V07 software update is designed specifically to address cybersecurity concerns and will ensure the integrity and confidentiality of Automatic Systems applications. With the new V07 software, updates will be delivered by means of an encrypted file.

  • QCS7230 System-on-Chip (SoC)

    QCS7230 System-on-Chip (SoC)

    The latest Qualcomm® Vision Intelligence Platform offers next-generation smart camera IoT solutions to improve safety and security across enterprises, cities and spaces. The Vision Intelligence Platform was expanded in March 2022 with the introduction of the QCS7230 System-on-Chip (SoC), which delivers superior artificial intelligence (AI) inferencing at the edge.

  • ResponderLink

    ResponderLink

    Shooter Detection Systems (SDS), an Alarm.com company and a global leader in gunshot detection solutions, has introduced ResponderLink, a groundbreaking new 911 notification service for gunshot events. ResponderLink completes the circle from detection to 911 notification to first responder awareness, giving law enforcement enhanced situational intelligence they urgently need to save lives. Integrating SDS’s proven gunshot detection system with Noonlight’s SendPolice platform, ResponderLink is the first solution to automatically deliver real-time gunshot detection data to 911 call centers and first responders. When shots are detected, the 911 dispatching center, also known as the Public Safety Answering Point or PSAP, is contacted based on the gunfire location, enabling faster initiation of life-saving emergency protocols.