Spatio-Temporal Relationship Match: Video Structure Comparison for Recognition of Complex Human Activities

Human activity recognition is a challenging task, especially when its background is unknown or changing, and when scale or illumination differs in each video. Approaches utilizing spatio-temporal local features have proved that they are able to cope with such difficulties, but they mainly focused on classifying short videos of simple periodic actions. In this paper, we present a new activity recognition methodology that overcomes the limitations of the previous approaches using local features. We introduce a novel matching, spatio-temporal relationship match, which is designed to measure structural similarity between sets of features extracted from two videos. Our match hierarchically considers spatio-temporal relationships among feature points, thereby enabling detection and localization of complex non-periodic activities. In contrast to previous approaches to ‘classify’ videos, our approach is designed to ‘detect and localize’ all occurring activities from co...

• Type: Conference
• Year: 2009
• Where: ICCV
• Authors: M. S. Ryoo1; J. K. Aggarwal
• Keywords: Complex Human Activities, Computer Vision, ICCV 2009, Spatio-Temporal Relationship Match