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Proceedings Paper

Robust region-merging technique for video sequences: spatiotemporal segmentation
Author(s): Riccardo Leonardi; Pier Angelo Migliorati; Giuseppe Tofanicchio
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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.

Paper Details

Date Published: 28 December 1998
PDF: 11 pages
Proc. SPIE 3653, Visual Communications and Image Processing '99, (28 December 1998); doi: 10.1117/12.334633
Show Author Affiliations
Riccardo Leonardi, Univ. of Brescia (Italy)
Pier Angelo Migliorati, Univ. of Brescia (Italy)
Giuseppe Tofanicchio, Univ. of Brescia (Italy)


Published in SPIE Proceedings Vol. 3653:
Visual Communications and Image Processing '99
Kiyoharu Aizawa; Robert L. Stevenson; Ya-Qin Zhang, Editor(s)

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