| Paper: | IMDSP-P10.2 | ||
| Session: | Video Segmentation and Tracking | ||
| Time: | Thursday, May 18, 10:00 - 12:00 | ||
| Presentation: | Poster | ||
| Topic: | Image and Multidimensional Signal Processing: Video Segmentation and Tracking | ||
| Title: | Probabilistic Spatio-Temporal Video Object Segmentation Incorporating Shape Information | ||
| Authors: | Rakib Ahmed, Gour C. Karmakar, Laurence S. Dooley, Monash University, Australia | ||
| Abstract: | From a video object segmentation perspective, using a joint spatio-temporal strategy is superior to processing with priority in either the spatial or temporal domains, as it considers a video sequence as a spatio-temporal grouping of pixels. However, existing spatio-temporal object segmentation techniques consider only pixel features, which tend to limit their performance in being able to segment arbitrary shaped objects. To address this limitation requires a new strategy for embedding generic shape information seamlessly into the segmentation process and this paper presents a new shape-based probabilistic spatio-temporal algorithm that achieves this objective. Experimental results using a number of standard video test sequences reveal a considerable performance improvement in being able to segment arbitrary shaped video objects in comparison with other contemporary space-time based video segmentation methods. | ||
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