Avigilon Appearance Search

Avgilon Appearance Search

Avigilon Appearance Search™ video analytics technology is a sophisticated deep learning AI search engine for video. It sorts through hours of video with ease, to quickly locate a specific person or vehicle of interest. Appearance Search can improve incident response time and enhance forensic investigations by helping operators compile robust video evidence, create a powerful narrative of events, and reveal a vehicle or individual’s route or last-known location.

Avigilon Appearance Find

Integrated Solution

Integrated with Avigilon Control Center (ACC) software, Avigilon cameras with self-learning video analytics and select Avigilon Network Video Recorders (NVRs).

Initiate Searches Based On Physical Descriptions

Allows operators to search for a person by selecting certain specific physical descriptions, including clothing color, gender and age categorization.

Search Across Multiple Sites

Initiate a search for a person or vehicle of interest across one site, then continue the search for the same subject of interest by seamlessly transitioning from one site to the next site that uses the same version of ACC software.

Face Analytics Included In Search

Incorporating the unique characteristics of a person’s face enables the Appearance Search technology to understand that it is searching for the same person, even if items such as their clothing change over time.

Playback, Bookmark and Export Tools

Build a comprehensive set of video evidence from multiple video sources, to create a powerful narrative of events.

Two Ways to Build Your Avigilon AI-Powered Solution

Avigilon AI-Powered Solution

Avigilon Integrated Solution

Enable Appearance Search by combining Avigilon H4 cameras with self-learning video analytics with our NVRs that are pre-loaded and pre-configured with ACC software.

ONVIF®-COMPLIANT SOLUTION

ONVIF®-Compliant Solution

Evolve your legacy Avigilon and third-party ONVIF-compliant camera systems with the Avigilon AI Appliance, adding patented self-learning video