Adaptive, Automated Real-time Event/Target Detection using Supervised Learning
Navy SBIR FY2012.1


Sol No.: Navy SBIR FY2012.1
Topic No.: N121-017
Topic Title: Adaptive, Automated Real-time Event/Target Detection using Supervised Learning
Proposal No.: N121-017-0017
Firm: Vecna Technologies Inc.
6404 Ivy Lane
Suite 500
Greenbelt, Maryland 20770
Contact: Neal Checka
Phone: (617) 674-8545
Web Site: www.vecna.com
Abstract: Human operators must closely monitor video for simultaneous situational awareness and threat assessment. For instance, urban environments in a state of constant activity generate numerous visual cues, each of which must be examined so that potential security breaches do not go unnoticed. The need for constant vigilance places a significant burden on the human operator, invariably leading to fatigue and lapses in attention span. Vecna Robotics proposes a video event detection software tool, known as AESOP, that automatically detects time critical events in real-time. AESOP learns new events using a programming by example. With this technique, the analyst teaches the software tool new events by demonstrating actions on concrete examples. Once trained, AESOP processes incoming video and proactively identifies user-defined events in real-time while also indexing the video to simplify forensic analysis. Using state-of-the-art computer vision algorithms, the system identifies and tracks all targets in the scene. Characteristic features for each target are extracted over time yielding feature trajectories which are then efficiently matched to the trained event trajectories. An easy-to-use user interface allows the analyst to visualize and confirm detected events quickly. Furthermore, AESOP's accuracy can improve by incorporating the confirmed detected events into the training set.
Benefits: The resulting system will represent a substantial breakthrough providing benefits to a wide array of applications in video surveillance and activity monitoring. This technology has potential to be a real, effective force multiplier for law enforcement agencies. For example, the software can monitor video feeds in real-time to detect activities of interest and direct human attention only to areas needing further scrutiny - freeing up law enforcement to be out on the street where they can be of most use.

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