EM motion segmentation based on MRF model

Jie Wei; Izidor Gertner

doi:10.1117/12.499593

16 September 2003 EM motion segmentation based on MRF model

Jie Wei, Izidor Gertner

Proceedings Volume 5094, Automatic Target Recognition XIII; (2003) https://doi.org/10.1117/12.499593
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

In our earlier work, a Two-Pass motion estimation Algorithm (TPA) was developed to estimate a motion field for two adjacent frames in an image sequence where contextural constraints are handeled by several Markov Random Fields (MRFs) and the most A Posteriori (MAP) configuration is taken to be the resulting motion field. Currently in the disciplines of digital library and video processing of utmost interest are the extraction and representation of visual objects. Instead of estimating motion field, in this paper we focus on segmenting out visual objects based on spatial and temporal properties present in two contiguous frames under the MRF-MAP-MFT scheme. To achieve object segmentation, within the framework of EM optimization a novel concept "motion boundary field" is introduced which can turn off interactions between different object regions and in the mean time remove spurious objerct boundaries. Furthermore, in light of the generally smooth and slow velocities in-between two contiguous frames, we found that in the process of calculating matching blocks, assigning different weights to different locations can result in better object segmentation.

Citation Download Citation

Jie Wei and Izidor Gertner "EM motion segmentation based on MRF model", Proc. SPIE 5094, Automatic Target Recognition XIII, (16 September 2003); https://doi.org/10.1117/12.499593

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