1. Motion Object Segmentation, Recognition and Tracking Huiqiong Chen; Yun Zhang; Derek Rivait Faculty of Computer Science Dalhousie University

2. Aims Goal of this research To achieve a robust, low-complexity and accurate method for motion segmentation by using perceptual organization principles Motivation The role of Perceptual organization in vision is critical to success. Proposed method: GET based motion segmentation Applications Video coding and compression Video surveillance Military target detection Medical Imaging Traffic Monitoring

3. GET-based Motion S egmentation: System Architecture

4. System Data Flow

5. Sample 1: Walk Man Sequence Original frame GET Map MGET groups Segmentation result

6. Sample 2: Express Way Sequence Original frame GET Map MGET groupsSegmentation result

7. Goal develop a practical solution to extract license plate of moving vehicles so that the license plate of each vehicle passing by can be identified automatically. Key idea combine motion tracking with region detection use application specific knowledge to guide for the target region detection: region shape, ratio of width to height use knowledge previously discovered to generate a Region of Interest which focuses tracking to relevant areas. License Recognition and Tracking

8. License Recognition and Tracking (Cont’d) Original frame GET feature map

9. License Recognition and Tracking (at night) Original frame License plate Region of Interest

10. License Recognition and Tracking (During the Day) License plate Original frame Region of Interest MGETs