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A Robust Region Merging Technique for Video Sequence Spatio-Temporal Segmentation

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14/07/12 17.15 | Publications: SPIE

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Robust region-merging technique for video

sequences: spatiotemporal segmentation

(Proceedings Paper)

Author(s): Riccardo Leonardi; Pier A. Migliorati; Giuseppe Tofanicchio Date: 28 December 1998 ISBN: 9780819431240 PDF Member: $18.00 | Non-member: $18.00 Hard Copy Member: $24.00 | Non-member: $24.00 Proceedings Vol. 3653

Visual Communications and Image Processing '99, Kiyoharu Aizawa; Robert L. Stevenson; Ya-Qin Zhang, Editors, pp.1258-2827

Date: 28 December 1998 ISBN: 9780819431240 Paper Abstract

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. DOI: 10.1117/12.334633

Current SPIE Digital Library subscribers click here to download this paper. © SPIE - Downloading of the abstract is permitted for personal use only. See Terms of Use

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