Probabilistic Spatio-Temporal Video Object Segmentation Incorporating Shape Information

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