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video sequence segmentation using genetic algorithms

PATTERN RECOGNITION LETTERS 2002年第7期23卷 843-863页

作者： Kim, EY Park, SH Hwang, SW Kim, HJ Chosun Univ Dept Comp Engn Dong Gu Kwangju 501759 South Korea Kyungpook Natl Univ Dept Comp Engn Puk Gu Taegu South Korea

This paper proposes a new video sequence segmentation method based on the genetic algorithm (GA) that can improve computational efficiency. The computation is distributed into chromosomes that evolve using distributed genetic algorithms (DGAs). Each chromosome consists of a label and feature vector. The label is used as the region number for the pixel where the chromosome is located. Based on the temporal correlation between two consecutive frames in a video sequence, the segmentation of a frame is successively obtained using the segmentation result of the previous frame. In addition to eliminating redundant computation, only unstable chromosomes corresponding to moving object parts are evolved. Experimental results confirm the effectiveness of the proposed method. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： video sequence segmentation distributed genetic algorithm temporal correlation

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Automatic moving object and background separation

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SIGNAL PROCESSING 1998年第2期66卷 219-232页

作者： Neri, A Colonnese, S Russo, G Talone, P Univ Rome 3 Dept Elect Engn I-00146 Rome Italy

In this paper, we propose a segmentation method of reduced computational complexity aimed at separating the moving objects from the background in a generic video sequence. This task may be accomplished at the coder site to support the functionalities foreseen by new multimedia scenarios, and in particular the content-based functionalities focused by the MPEG-4 activity, allowing the user to access and decode single objects of a video sequence. The proposed algorithm discriminates between background and foreground by means of a higher-order statistics (HOS) significance test performed on a group of inter-frame differences, followed by a motion detection phase, producing a binary segmentation map. The HOS threshold is adaptively changed, based on the estimated background activity and on the potential presence of slowly moving objects. The map is refined by a final regularization stage implemented by means of a cascade of morphological filters. The algorithm performance were tested through the wide experimental activity carried out during the ISO MPEG-4 N2 Core Experiment on Automatic segmentation Techniques, in which the authors are currently involved. Typical results obtained on MPEG4 sequences are here shown, in order to illustrate the segmentation algorithm performance. (C) 1998 Elsevier Science B.V. All rights reserved.

关键词： video sequence segmentation HOS motion detection MPEG-4

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Automatic segmentation of moving objects for video object plane generation

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR video TECHNOLOGY 1998年第5期8卷 525-538页

作者： Meier, T Ngan, KN Univ Western Australia Dept Elect & Elect Engn Visual Commun Res Grp Perth WA 6907 Australia

The new video coding standard MPEG-4 is enabling content-based functionalities. It takes advantage of a prior decomposition of sequences into video object planes (VOP's) so that each VOP represents one moving object. A comprehensive review summarizes some of the most important motion segmentation and VOP generation techniques that have been proposed. Then, a new automatic video sequence segmentation algorithm that extracts moving objects is presented. The core of this algorithm is an object tracker that matches a two-dimensional (2-D) binary model of the object against subsequent frames using the Hausdorff distance. The best match found indicates the translation the object has undergone, and the model is updated every frame to accommodate for rotation and changes in shape. The initial model is derived automatically, and a new model update method based on the concept of moving connected components allows for comparatively large changes in shape. The proposed algorithm is improved by a filtering technique that removes stationary background. Finally, the binary model sequence guides the extraction of the VOP's from the sequence. Experimental results demonstrate the performance of our algorithm.

关键词： content-based functionalities MPEG-4 object tracking video object planes video sequence segmentation

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AUTOMATIC segmentation OF video OBJECT PLANES IN MPEG-4 BASED ON SPATIO-TEMPORAL INFORMATION

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Journal of Electronics(China) 2004年第3期21卷 206-212页

作者： XiaJinxiang HuangShunji DeptofElectronlcEngineering UESTofChinaChengdu610054

segmentation of semantic video Object Planes (VOP's) from video sequence is a key to the standard MPEG-4 with content-based video coding. In this paper, the approach of automatic segmentation of VOP's Based on Spatio-Temporal Information (SBSTI) is *** proceeding results demonstrate the good performance of the algorithm.

关键词： video sequence segmentation video Object Plane (VOP) Based on spatiotemporal information MPEG-4

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