Robust object pose estimation from feature-based stereo

doi:10.1109/TIM.2006.876521

Robust object pose estimation from feature-based stereo

2006-08-01

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DOI：10.1109/TIM.2006.876521

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Abstract

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This paper addresses the problem of computing the three-dimensional (3-D) path of a moving rigid object using a calibrated stereoscopic vision setup. The proposed system begins by detecting feature points on the moving object. By tracking these points over time, it produces clouds of 3-D points that can be registered, thus giving information about the underlying camera motion. A novel correction scheme that compensates for the accumulated error in the computed positions by automatic detection of loop-back points in the movement of the object is also proposed. An application to object modeling is presented in which a handheld object is moved in front of a camera and is reconstructed using silhouette intersection.

Keywords:

camera calibration

feature matching

feature tracking

pose estimation

shape-from-silhouette

stereovision

three-dimensional (3-D) reconstruction

Robust object pose estimation from feature-based stereo

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