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This paper describes developing of an occlusion robust tracking algorithm of pedestrians in the panning images by the combination between the S-T MRF model and pattern recognition methods of Snakes and HOG classifier. Tracking in panning images would extend the field of view of single camera. In addition, an algorithm to match pedestrians between cameras that have overlapping area with each other...
This paper presents approach for an automated surveillance system which performs human detection and tracking across multiple non-overlapping cameras. Emphasis is put at single camera level where motion based segmentation is achieved using optical flow estimation. Feature matching and region-based shape descriptors are used for tracking. The proposed approach then extends feature and region-based...
In this paper, we designed a simple and fast visual surveillance system to track human position and to determine if any abnormal behavior like wall climbing and falling happened. By taking both time and background difference into considerations, illumination effects could be greatly reduced while calculating motion masks. Refinements including holes filling, shadow removal, and noise reduction are...
Matching of single individuals as they move across disjoint camera views is a challenging task in video surveillance. In this paper, we present a novel algorithm capable of matching single individuals in such a scenario based on appearance features. In order to reduce the variable illumination effects in a typical disjoint camera environment, a cumulative color histogram transformation is first applied...
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