Block motion model for optical flow with smoothness prior function

被引：0
|
作者：
Tandjung, Stephanus Surijadarma [1 ]
Soon, Seah Hock [2 ]
Kemao, Qian [2 ]
机构：
[1] Tokyo Inst Technol, NTT Comm, BeyondLSI Inc, Tokyo 152, Japan
[2] Nanyang Technol Univ, Sch Comp Engn, Singapore 639798, Singapore
来源：
2006 9TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION, VOLS 1- 5 | 2006年
关键词：
optical flow; motion estimation; maximum a posterior probability; Markov random field;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An explicit constraint is introduced into the Lucas-Kanade gradient based block motion model. This constraint helps the estimation process to consider surrounding motion vectors during its calculation. Consequently a better motion field can be produced than that by the original block motion model. Further, a discontinuity adaptive function is introduced into the Lucas-Kanade equation, which helps to preserve the discontinuities of motion fields.
引用
收藏
页码：1652 / +
页数：3
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