Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Tracking of Moving Objects in Video Through Invariant Features in Their Graph Representation | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2008 Article ID 328052 14 pages doi 2008 328052 Research Article Tracking of Moving Objects in Video Through Invariant Features in Their Graph Representation O. Miller 1 A. Averbuch 2 and E. Navon2 1 ArtiVision Technologies Pte. Ltd. 96 Robinson Road 13-02 Singapore 068899 2 School of Computer Science Tel Aviv University Tel Aviv 69978 Israel Correspondence should be addressed to A. Averbuch amir@ Received 21 July 2007 Accepted 10 July 2008 Recommended by Fatih Porikli The paper suggests a contour-based algorithm for tracking moving objects in video. The inputs are segmented moving objects. Each segmented frame is transformed into region adjacency graphs RAGs . The object s contour is divided into subcurves. Contour s junctions are derived. These junctions are the unique signature of the tracked object. Junctions from two consecutive frames are matched. The junctions motion is estimated using RAG edges in consecutive frames. Each pair of matched junctions may be connected by several paths edges that become candidates that represent a tracked contour. These paths are obtained by the fc-shortest paths algorithm between two nodes. The RAG is transformed into a weighted directed graph. The final tracked contour construction is derived by a match between edges subcurves and candidate paths sets. The RAG constructs the tracked contour that enables an accurate and unique moving object representation. The algorithm tracks multiple objects partially covered occluded objects compounded object of merge split such as players in a soccer game and tracking in a crowded area for surveillance applications. We assume that features of topologic signature of the tracked object stay invariant in two consecutive frames. The algorithm s complexity depends on RAG s edges and not on the image s size. Copyright 2008 O. Miller et al. This is an open access article distributed under the
