analysis and query of person-vehicle interactions in homography domain
This paper presents an efficient and robust paradigm for analysis and query of moving-object interactions in planar homography domain.People and vehicle activities/interactions are analyzed for situational awareness by using a multi-perspective approach.Planar homography constraints are exploited to extract view-invariant object features including footage area and velocity of objects on the ground plane. Spatio-temporal relationships between person-and vehicle-tracks are represented by a semantic event grammar. Semantic-level information of the situation is achieved with the anticipation of possible directions of near-future tracks using piecewise velocity history. An efficient query paradigm is proposed by histogram-based approximation of probability density functions of objects and by quad-tree indexing. Experimental data show promising results.Our framework can be applied to applications for enhanced situational awareness such as disaster prevention,human interactions in structured environments,and crowd movement analysis in wide-view areas.
human interaction event recognition video surveillance motion scene understanding