28 December 1998 Robust region-merging technique for video sequences: spatiotemporal segmentation
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The segmentation of video sequences into regions underlying a coherent motion is one of the most important processing in video analysis and coding. In this paper, we propose a reliability measure that indicates to what extent an affine motion model represents the motion of an image region. This reliability measure is then proposed as a criterion to coherently merge moving image regions in a Minimum Description Length (MDL) framework. To overcome the region-based motion estimation and segmentation chicken and egg problem, the motion field estimation and the segmentation task are treated separately. After a global motion compensation, a local motion field estimation is carried out starting from a translational motion model. Concurrently, a Markov Random Field model based algorithm provides for an initial static image partition. The motion estimation and segmentation problem is then formulated in the view of the MDL principle. A merging stage based on a directed weighted graph gives the final spatio-temporal segmentation. The simulation results show the effectiveness of the proposed algorithm.
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Riccardo Leonardi, Riccardo Leonardi, Pier Angelo Migliorati, Pier Angelo Migliorati, Giuseppe Tofanicchio, Giuseppe Tofanicchio, } "Robust region-merging technique for video sequences: spatiotemporal segmentation", Proc. SPIE 3653, Visual Communications and Image Processing '99, (28 December 1998); doi: 10.1117/12.334633; https://doi.org/10.1117/12.334633

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