A Video ATR System for Vehicle Classification and Recognition

ImageCorp, Inc. proposes to design and develop a deployable video automatic target recognition (ATR) system for vehicle classification and recognition using a single video stream. The system will be built by improving the performance of the existing Phase I prototype system which was based on fusing frame-based decisions made either by a support vector machine or a Hausdorff metric based classifier and did not achieve full temporal integration of video frames. Experiments with real video streams illustrated many remaining challenges. Three major areas have been identified for further development and system integration in Phase II: (1) refining the Phase I software by adding capabilities for shadow detection, pose estimation, detection and tracking of multiple vehicles under occlusions, and simultaneous tracking and verification using particle filters; (2) investigating the utilization of CAD models to generate 3D fingerprints, enable classification of a much larger class of vehicles containing subtle variations, and assist target mensuration; and (3) addressing system integration issues related to real-time classification. Optimal video camera configuration will be studied, and system performance will be comprehensively evaluated. Two demonstrations will be performed using the deployed prototype system operating in realistic outdoor scenarios using live videos.