Video Segmentation Descriptors for Event Recognition

This paper presents a new video motion descriptor based on a multi-scale video segmentation to provide a multi-layered output as well as connections with the rich interactions that occur between objects at the semantic level. We also put the emphasis on relationships between motion clusters by providing a new relative motion descriptor encapsulating relative motion patterns within a local spatio-temporal neighborhood. Experimental results on the challenging TRECVID MED11 event recognition dataset validate the approach.