BriefCam BootCamp

Watch this video to learn how the RESEARCH module of the BriefCam Video Analytics Platform now offers face re-identification across multiple cameras, so that the technology can be leveraged to identify individual anonymized faces and aggregate the data over time to uncover intelligence about unique visits, repeat visits, bounced visits, and average visit duration.  

To ensure highly accurate Face Recognition, it is crucial to have a face image that has high resolution, i.e., pixel count. That is why BriefCam’s face recognition technology requires a minimum face image size of 24×24 pixels. Watch this video to learn the various factors that can affect the resolution of images: camera resolution, lighting, […]

The National Institute for Standards and Technology (NIST) has created two standard datasets of images to test facial recognition technologies: 1) “In the wild” (LFW) images that are more typical of images captured in video surveillance, and 2) constrained (IJB-8) images that are based on celebrity photos from media outlets. This video explains how BriefCam […]

Watch this video to learn how different camera types (fisheye, multi-sensor, infra-red, thermal), as well as camera placement, lighting, and focus can affect the quality of face images in Face Recognition technology. Learn useful tips about resolution, lighting, shutter speed, focus, and camera angle to collect high-quality images, which will help ensure the accuracy of […]

Facial recognition technology has crucial public safety applications, such as cracking cold cases, thwarting potential terrorist attacks, finding missing persons, investigating human trafficking, and solving thousands of other types of crimes. When combined with human oversight, the technology overcomes human biases and provides accurate data to augment human observations. Watch this video to understand BriefCam’s […]

This video explains the several technology factors that enable high accuracy for “in the wild” Facial Recognition deployment. Factors include camera type placement, focus, and position, as well as the light source. Other variables include resolution of each face image, framerate, bitrate, and speed of the people as they pass by the camera. For optimal […]

There are more than 350 million video surveillance cameras worldwide recording around the clock, every day, producing overwhelming amounts of video data that is largely untouched. What if you could drive exponential value from your video content by making it searchable, actionable, and quantifiable? • Decisions would be truly data-driven • Crimes would be solved […]

Watch this video to see how BriefCam enables an operator to upload only watchlist images that have a high-quality score when setting up real-time Face Recognition alerts. This helps ensure greater accuracy when comparing watchlist images to possible matches in real-time video feeds. The system will indicate possible matches, with side-by-side comparisons of the watchlist […]

Learn how BriefCam’s face quality scoring functionality allows operators to select a reference face image from video footage, and then search for matching images. The software detects faces in a scene and scores the quality of the face image. The scoring system helps users select the highest quality images when conducting side-by-side comparisons of potential […]

Learn how BriefCam Face Recognition that is powered by Deep Neural Networks (DNNs) is able to verify or identify a person from a digital image or a video frame from a video source. This video explains how BriefCam curates DNNs with diverse training sets to prevent biases, and adds other workflow techniques to compensate for […]

Learn how to use BriefCam to create a Face Recognition watchlist, and easily upload multiple image files into it. Each identity can have more than one image associated with it, to provide operators with a choice of quality images to match against it.

This video demonstrates how BriefCam’s Face Recognition function searches for faces that are on a digital watchlist. Each face on a digital watchlist has an identity name and number. The system can identify face matches in archived footage or real-time footage, and then display face matches side-by-side so that operators can compare the images.

BriefCam’s fully integrated License Plate Recognition capability enables managers and security teams to track vehicle activities in a fleet logistics or operations center, and locate particular vehicles by license plate number. Operators can track all vehicle activity on premises, such as vehicle entrances and exits, as well as off-premises activities, such as the duration of […]

This video explains how BriefCam’s platform approach helps cities reduce crime, spur economic growth and ensure public safety: BriefCam’s patented VIDEO SYNOPSIS solution enables granular, rapid review of footage to conduct post-incident investigations with speed and accuracy; Real-time analytics and alerts help staff attain situational awareness so they can rapidly respond to developing situations; RESEARCH reports […]

See this video to understand how BriefCam’s License Plate Recognition capability includes the use of wildcards to locate vehicles, even if end-users have only a partial license plate number. Learn how partial plate numbers may be added to a digital watchlist to search either archived footage or real-time camera footage, and how operators can receive […]

This video explains how BriefCam’s License Plate Recognition filter helps law enforcement officers locate a vehicle of interest, using a whole or partial plate number. Operators can conduct a forensic review that locates the vehicle in archived footage; or, respond in real-time by creating a live tracking watchlist to continuously track that vehicle; or, deliver […]

Watch this video to learn how BriefCam’s Face Recognition is unique in its class because of its ability to detect features, assess the quality of a face images, and feature vector matching – as a fully integrated capability of its comprehensive and extensible video analytics platform. This results in more accurate matches, but also faster […]

This video explains how BriefCam’s Face Recognition capability scores the quality of detected faces in terms of accuracy and angle, to help users determine which facial images are the most accurate and should be included as a reference photo when conducting a real-time or forensic search for an individual. It also demonstrates how users can […]

This video explains the differences between constrained vs. unconstrained (in the wild) Face Recognition. Learn how the BriefCam video analytics platform achieves face recognition by comparing images on a preset watchlist to faces in the video surveillance footage, despite challenging and variable conditions such as varied camera resolutions, lighting and angles. Learn more about BriefCam’s […]

Learn how BriefCam video analytics software conducts unconstrained (in the wild) facial recognition by comparing images on a preset watchlist to faces in video surveillance footage. This enables users to search, filter and alert on faces detected in video, as well as cross-camera face tracking for unique traffic analytics. Learn more about BriefCam’s facial recognition […]