Title :
Incorporation of Texture Information for Joint Spatio-Temporal Probabilistic Video Object Segmentation
Author :
Ahmed, Rakib ; Karmakar, Gour C. ; Dooley, Laurence S.
Author_Institution :
Monash Univ., Clayton
fDate :
Sept. 16 2007-Oct. 19 2007
Abstract :
Embedding textural information into the probabilistic spatio-temporal (PST) video object segmentation is very important for achieving better segmentation, since this is one of the key perceptual attributes of any object. Existing video segmentation techniques however, ignore this feature because of the underlying difficulty in defining and hence characterizing a texture, which theoretically limits their segmentation performance. To address this problem, this paper proposes a new video object segmentation algorithm that involves a strategy to seamlessly incorporate texture information as a pixel feature in the PST framework. Experimental results for a variety of standard test sequences reveal a significant performance improvement in the quality of the video object segmentation achieved in comparison with the original PST method.
Keywords :
image segmentation; image sequences; image texture; video signal processing; image sequence analysis; joint spatiotemporal probabilistic video object segmentation; pixel feature; texture information; Image analysis; Image segmentation; Image sequence analysis; Information technology; Machine vision; Motion estimation; Object segmentation; Surface texture; Testing; Video sequences; Image sequence analysis; image texture; joint spatio-temporal; machine vision; video segmentation;
Conference_Titel :
Image Processing, 2007. ICIP 2007. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-1437-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2007.4379579