Unsupervised segmentation of highly dynamic scenes through global optimization of multiscale cues
We introduce a global optimization of weighted total variation energy functional. The energy combines motion and spectral boundaries with object inside mappings. Alternating direction convex optimization provides high-quality salient mapping. Integrating mapping with MRF facilitates sequential combination of multiscale cues. Feasibility and superiority are demonstrated in segmenting highly dynamic scenes.
unsupervised segmentation dynamic scene global optimization image sequence segmentation