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.
AI-powered facial recognition technology, within Avigilon Control Center (ACC), helps you accelerate response times by quickly identifying people of interest. Facial recognition offers the context to make better-informed decisions that empower you to respond to events proactively.
People of interest are identified based on one or more secure watch lists managed by authorized users at your organization. Users can populate and manage multiple watch lists by either adding faces from Appearance Search, uploading reference images, or finding appearances of the person through recorded video. The Identity Retention settings also allow face match events and Appearance Search metadata to be aged out ahead of the video if desired.
Focus of Attention
Focus of Attention (FoA) introduces a new concept in video monitoring and brings to the user a more intuitive way to consume information about potential security events.
The FoA interface shows a comprehensive topology of your entire camera population, with nodes that represent each camera, grouped in a honeycomb formation according to how cameras are organized in the Site View (system tree) in Avigilon Control Center (ACC).
Powered by Avigilon cameras and appliances with self-learning and next-generation analytics, the FoA interface uses artificial intelligence to detect and flag events that may require your attention, highlighting them visually in color-coded nodes to indicate different levels of importance:
- Blue: Motion Detected
- Teal: Unusual Motion Detected or Analytic Event
- Yellow: Unusual Activity Detected, Face Watch List Match Event, License Plate Watch List Match Event, or No Face Mask Detected
- Red: Alarm
License Plate Recognition (LPR) Analytics
Accurately Capture Vehicle License Plates
Avigilon LPR analytics automatically reads license plate information from vehicles, linking it to live and recorded video. This enables security operators to search and quickly find specific captured license plate video for verification and investigation.
Create and import several license plate watch lists so that ACC™ software can provide you with security alerts, helping you take decisive action when needed.
Next-Generation Video Analytics
Our most advanced analytics technology uses neural networks to power self-learning video analytics, delivering improved accuracy in both perimeter protection and in crowded, indoor environments.
IMPROVED DETECTION SPEED AND ACCURACY
Added processing power enables the tracking and classification of over 50 objects. Previous analytics classified objects only when they were moving, now objects are additionally classified if they remain stationary.
IMPROVED ANALYTIC EVENT GENERATION AND APPEARANCE SEARCH RESULTS
More processing power enhances Avigilon Appearance Search™ technology by expanding the ability to search for a person or vehicle in both crowded and indoor environments.
EXPANDED OBJECT CLASSIFICATION
Avigilon video analytics go beyond people and vehicles to include cars, trucks, buses, motorcycles, and bicycles.
Self-Learning Video Analytics
Through the use of advanced pattern-based analytics and teach-by-example technology, Avigilon video analytics are designed to increase the productivity of security personnel while making monitoring more affordable and efficient.
Avigilon’s self-learning analytics extends the effectiveness of your security personnel by providing effective monitoring and enabling proactive, real-time response from your team. Built from the ground up to manage high-definition video, Avigilon offers analytics embedded in Avigilon cameras up to 5K (16 MP) resolution.
Avigilon’s advanced video pattern detection technology is able to accurately recognize the movements of people and vehicles while ignoring motion not relevant to a scene. Embedded into cameras up to 5K (16 MP), the system’s ability to constantly learn reduces false positives and helps ensure alerts are meaningful, which avoids wasted time and improves efficiencies.
Unusual Activity Detection
Uncover Atypical Events that May Go Unnoticed
Unusual Activity Detection (UAD) provides new edge-based intelligence that uses advanced AI technology. It is designed to enable the detection of atypical activities, such as people and vehicles traveling at faster speeds or are in unusual locations and alert operators.
FILTERED RECORDED TIMELINE SEARCH
Helps you quickly review large amounts of video by filtering ACC’s timeline to only highlight the periods where Unusual Activity Detection (UAD) events have occurred.
EMBEDDED ON H5A PLATFORM CAMERAS
UAD technology is embedded in the Avigilon H5A camera line, offering high-powered AI capabilities on our flagship line of cameras.
Unusual Motion Detection
Reveal Events that Might Otherwise Be Missed
Unusual Motion Detection (UMD) is an advanced AI technology that brings a new level of automation to security. Without any predefined rules or setup, UMD technology is able to continuously learn what typical activity in a scene looks like, and then detect and flag unusual motion. This allows operators to filter through large amounts of recorded video faster when using Avigilon Control Center (ACC) video management software, as it flags atypical events that may need further investigation, helping to reduce hours of work to minutes.