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Technical Program
Paper Detail
| Paper: | WA-P1.10 |
| Session: | Image and Video Segmentation |
| Time: | Wednesday, October 11, 09:40 - 12:20 |
| Presentation: |
Poster
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| 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. |
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