Using multiple-hypothesis disparity maps and image velocity for 3-D motion estimation

被引：0

作者：

Demirdjian, D ^{[1
]}

Darrell, T ^{[1
]}

机构：

[1] MIT, AI Lab, Cambridge, MA 02139 USA

来源：

IEEE WORKSHOP ON STEREO AND MULTI-BASELINE VISION, PROCEEDINGS | 2001年

关键词：

D O I：

10.1109/SMBV.2001.988770

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we explore a multiple hypothesis approach to estimating rigid motion from a moving stereo rig. More precisely, we introduce the use of Gaussian mixtures to model correspondence uncertainties for disparity and velocity (optical flow) estimation. We show some properties of the disparity space and show how rigid transformations can be represented. An algorithm derived from standard random sampling-based robust estimators, that efficiently estimates rigid transformations from multi-hypothesis disparity maps and velocity fields is given.

引用

页码：121 / 128

页数：8

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