ICIP 2006, Atlanta, GA
 

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Paper Detail

Paper:WA-P1.10
Session:Image and Video Segmentation
Time:Wednesday, October 11, 09:40 - 12:20
Presentation: Poster
Topic: Image & Video Segmentation: Statistical methods
Title: REGION-BASED SHAPE INCORPORATION FOR PROBABILISTIC SPATIO-TEMPORAL VIDEO OBJECT SEGMENTATION
Authors: Rakib Ahmed; Monash University 
 Gour Chandra Karmakar; Monash University 
 Laurence Dooley; Monash University 
Abstract: Embedding generic shape information into probabilistic spatio-temporal video object segmentation is of pivotal importance to achieving better segmentation, since it provides valuable perceptual clues for humans in both distinguishing and recognising objects. Recently a probabilistic spatio-temporal video object segmentation algorithm incorporating shape information has been proposed, though since it is restricted to only pixel features, the probability of a pixel belonging to a certain cluster is directly correlated with its spatial location, which theoretically limits the segmentation performance of the technique. To address this problem, this paper proposes a new probabilistic spatio-temporal video object segmentation algorithm that incorporates generic shape information based on its region. Experimental results reveal a significant performance improvement in arbitrary-shaped video object segmentation compared with other contemporary methods for a variety of standard video test sequences.