Model based segmentation of motion fields in compressed video sequences using partition projection and relaxation
Siripong Treetasanatavorn, Uwe Rauschenbach, Jörg Heuer, André Kaup · 2005
In the context of visual signal analysis for media adaptation, this paper presents a stochastic method for sementation of motion vector fields or as known as displacement fields in compressed videos. The addressed field sequence is analysed and partitioned to temporally associated, motion-semantic regions by three analysis steps. The global motion based reliability analysis assesses the reliability extent of each encoded displacement vector. Upon the measure array, an initial partition is approximated by the region displacement prediction. The subsequent relaxation procedure optimises the partition shape, coverage, and location using the stochastic motion coherency model and the second-order random field based contour smoothness. The visually convincing results are demonstrated from the standard sequences.