{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,2]],"date-time":"2025-10-02T06:09:17Z","timestamp":1759385357961},"reference-count":22,"publisher":"World Scientific Pub Co Pte Lt","issue":"06","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2008,9]]},"abstract":"<jats:p> We present a shape-based method for automatic people detection and counting without any assumption concerning camera motion. In order to evaluate the robustness of the proposed method, we apply it for classifying athletics videos into two classes: videos of individual and videos of team sports. The videos used are real and characterized by dynamic and unconstrained environment. Moreover, in the case of team sport, we propose a shape deformations based method for running\/hurdling discrimination (activity recognition). Robust, adaptive and independent from color, illumination changes and the camera motion, the proposed features are combined in the Transferable Belief Model (TBM) framework providing a two-level (frames and shot) video categorization. Experimental results of 97% of accuracy for individual\/team sport categorization using a dataset of 252 real videos of athletic meetings, acquired by moving cameras under varying view angles, indicate the stability and the good performance of the proposed scheme. <\/jats:p>","DOI":"10.1142\/s0218001408006752","type":"journal-article","created":{"date-parts":[[2008,9,16]],"date-time":"2008-09-16T08:43:50Z","timestamp":1221554630000},"page":"1187-1213","source":"Crossref","is-referenced-by-count":11,"title":["SHAPE-BASED INDIVIDUAL\/GROUP DETECTION FOR SPORT VIDEOS CATEGORIZATION"],"prefix":"10.1142","volume":"22","author":[{"given":"COSTAS","family":"PANAGIOTAKIS","sequence":"first","affiliation":[{"name":"Computer Science Department, University of Crete, P. O. Box 2208, Heraklion, Greece"}]},{"given":"EMMANUEL","family":"RAMASSO","sequence":"additional","affiliation":[{"name":"GIPSA-Lab, Images and Signal Department, 46 av. F\u00e9lix Viallet, 38031 Grenoble, France"}]},{"given":"GEORGIOS","family":"TZIRITAS","sequence":"additional","affiliation":[{"name":"Computer Science Department, University of Crete, P. O. Box 2208, Heraklion, Greece"}]},{"given":"MICH\u00c8LE","family":"ROMBAUT","sequence":"additional","affiliation":[{"name":"GIPSA-Lab, Images and Signal Department, 46 av. F\u00e9lix Viallet, 38031 Grenoble, France"}]},{"given":"DENIS","family":"PELLERIN","sequence":"additional","affiliation":[{"name":"GIPSA-Lab, Images and Signal Department, 46 av. 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