Find and recover missing persons

Cities already rely on video content analytics solutions to identify, track, and recover missing persons. Facial recognition can significantly accelerate technology operators’ efforts by enabling them to add a reference photo provided by the missing person’s relatives and match it with past appearances of that face that have been captured on video. Using facial recognition to search video based on the approximate area and time the person disappeared, police can quickly understand the person’s movements before going missing, locate where the person was last seen on camera, and configure real-time alerts to trigger an alarm whenever face matches are identified. Police can immediately assess matches and confirm their accuracy, allowing the rapid deployment of responders to recover the missing person and, when relevant, apprehend the abductor.

Identify and track known offenders

Face matching can be used to enable police to track and identify past offenders suspected of perpetrating an additional crime. By using an image of an offender from within a video, an uploaded external image, or a national offenders repository, operators can use facial recognition to detect matches that appear in live video and quickly respond to suspicious behaviour.

Efficiently investigate and reduce crime

The same way face matching can be used to detect suspicious behaviour in real-time, it can be used to support investigators searching for video evidence in the aftermath of an incident. The ability to isolate the appearances of specific suspects and individuals is critical for accelerating investigators’ review of video evidence to pinpoint relevant details and understand how situations developed. When a suspect or perpetrator is not apprehended at the crime scene, this capability can also enable police to continue to search for their target by configuring real-time alerts for his or her appearances in the video, thereby curtailing the suspect’s ability to execute further crimes.

Manage city staff and optimise productivity

Facial recognition can also be used to drive productivity within city hall and ensure its workforce is effectively and efficiently serving the needs of the city residents. By tracking the appearances of city workers across the cameras at city hall, the city can easily verify and track attendance records. Similarly, they can use it to confirm that cleaning staff is performing the maintenance being reported as complete. From a customer service standpoint, cities can leverage video analytics to derive quantitative intelligence about traffic patterns at city hall, like when crowding occurs, how long visitors wait for service, or which city employees are most efficient in providing support. By visualising this video data in a dashboard, cities carefully assess performance and better manage employees.

As higher quality cameras have proliferated and video analytics technology has evolved, facial recognition has become more accurate, driving increased adoption. At the same time, cities and governments are still exploring how to balance the benefits of technology with the legal and regulatory concerns over its use. The laws governing the use of video surveillance and facial recognition vary from country to country, and when deploying such a system, it is important to comply with the applicable regulation. Cities continue to work with their technology producers, federal governments, and residents to navigate the use of face recognition, ensuring fairness, transparency, accountability, and privacy compliance.

Ultimately, says Convergint, the ideal facial recognition implementation in a city is one that is founded on residents’ trust in the city; the city’s continued demonstration of integrity around the use of the technology; and the technology’s impact in driving superior security, increased public safety, and streamlined city operations.