Title :
Multiple feature clustering algorithm for automatic video object segmentation
Author :
Wei, Wei ; Ngan, King N. ; Habili, Nariman
Author_Institution :
Dept. of Electron. Eng., Chinese Univ. of Hong Kong, China
Abstract :
In this paper, we present an automatic video segmentation algorithm for object-based coding, based on a k-medians clustering algorithm and 2D binary model. Firstly, the k-medians algorithm is employed to partition an image into a set of homogeneous regions. Then, a 2D binary model of the moving object is set up, which, combined with temporal and spatial information, guides the extraction process of the video object planes from the video sequence. The performance of the segmentation algorithm is illustrated by simulations carried out on standard video sequences.
Keywords :
feature extraction; image segmentation; motion estimation; video signal processing; VOP extraction process; automatic video object segmentation; homogeneous region partitioning; image partitioning; k-medians clustering algorithm; moving object 2D binary model; multiple feature clustering algorithm; object-based coding; video object planes; Clustering algorithms; Data mining; Image analysis; Image segmentation; Medical simulation; Object detection; Object segmentation; Partitioning algorithms; Video compression; Video sequences;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on
Print_ISBN :
0-7803-8484-9
DOI :
10.1109/ICASSP.2004.1326622
