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 Multiple Moving Object Detection for Fast Video Content Description in Compressed Domain | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 231930 15 pages doi 2008 231930 Research Article Multiple Moving Object Detection for Fast Video Content Description in Compressed Domain Francesca Manerba 1 Jenny Benois-Pineau 2 Riccardo Leonardi 1 and Boris Mansencal2 1 Department of Electronics for Automations DEA University of Brescia 25123 Brescia Italy 2 Laboratoire Bordelais de Recherche en Informatique LaBRI Universite Bordeaux 1 Bordeaux 2 CNRS ENSEIRB 33405 Talence Cedex France Correspondence should be addressed to Jenny Benois-Pineau Received 20 November 2006 Revised 13 June 2007 Accepted 20 August 2007 Recommended by Sharon Gannot Indexing deals with the automatic extraction of information with the objective of automatically describing and organizing the content. Thinking of a video stream different types of information can be considered semantically important. Since we can assume that the most relevant one is linked to the presence of moving foreground objects their number their shape and their appearance can constitute a good mean for content description. For this reason we propose to combine both motion information and regionbased color segmentation to extract moving objects from an MPEG2 compressed video stream starting only considering low-resolution data. This approach which we refer to as rough indexing consists in processing P-frame motion information first and then in performing I-frame color segmentation. Next since many details can be lost due to the low-resolution data to improve the object detection results a novel spatiotemporal filtering has been developed which is constituted by a quadric surface modeling the object trace along time. This method enables to effectively correct possible former detection errors without heavily increasing the computational effort. Copyright 2008 Francesca Manerba et al. This is an open access article distributed under the .
