Zooming In On Appearance Search Technology: AI In Electronic Security Systems

As we continue to examine AI tools in the electronic security systems industry, one that we touched on in a previous post which continues to stand out is Appearance Search Technology.

Used to identify and track individuals or objects across video surveillance footage based on their unique visual characteristics, Appearance Search Technology uses computer vision and machine learning algorithms to analyze features like clothing color, accessories, or vehicle make and model, enabling quick and precise searches.

This technology has transformed video surveillance from a reactive tool to a proactive system. By enabling rapid identification and tracking, it significantly improves response times during critical incidents such as identifying suspects or locating stolen items. It also facilitates predictive security by identifying suspicious behaviors or repeat appearances of flagged individuals, helping to prevent potential threats before they escalate. In large-scale systems like city surveillance or airports or college campuses, appearance search automates the process of reviewing hours of footage.

Our partner, Avigilon, is at the forefront of Appearance Search and has successfully deployed the technology as part of its comprehensive security solutions. In one example, the police department at Marian University in Indiana used Avigilon Appearance Search to capture a suspect driving at a high rate of speed across campus, then find where the vehicle went and ultimately identify the suspect, saving the department time and resources in tracking and, most importantly, avoiding potential injuries.

You can read all about Marian University’s use of Avigilon Appearance Search is this case study. Or check out this use case from Tampere Vocational College Tredu (Tredu) in Finland.