Model based segmentation of motion fields in compressed video sequences using partition projection and relaxation

被引：1

作者：

Treetasanatavorn, S ^{[1
]}

Rauschenbach, U ^{[1
]}

Heuer, J ^{[1
]}

Kaup, A ^{[1
]}

机构：

[1] Univ Erlangen Nurnberg, Chair Multimedia Commun & Signal Proc, D-91058 Erlangen, Germany

来源：

VISUAL COMMUNICATIONS AND IMAGE PROCESSING 2005, PTS 1-4 | 2005年 / 5960卷

关键词：

compressed video analysis for media adaptation; stochastic motion segmentation; stochastic object tracking;

D O I：

10.1117/12.631458

中图分类号：

TB8 [摄影技术];

学科分类号：

0804 ;

摘要：

In the context of visual signal analysis for media adaptation, this paper presents a stochastic method for segmentation of motion vector fields or as known as displacement fields in compressed videos. The addressed field sequence is analysed and partitioned to temporally associated, motion-semantic regions by three analysis steps. The global motion based reliability analysis assesses the reliability extent of each encoded displacement vector. Upon this measure array, an initial partition is approximated by the region displacement prediction. The subsequent relaxation procedure optimises the partition shape, coverage, and location using the stochastic motion coherency model and the second-order random field based contour smoothness. The visually convincing results are demonstrated from the standard sequences.

引用

页码：111 / 120

页数：10

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