Recursive estimation of motion and a scene model with a two-camera system of divergent view

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摘要

This paper deals with recursive reconstruction of a scene model from unknown motion of a two-camera system capturing the images of the scene. Single camera systems with a relatively small field of view have limited accuracy because of the inherent confusion between translation and rotation. Estimation results from the stereo camera systems are also compromised due to this confusion if the systems require the fields of view to intersect for stereo correspondence. The cameras constituting the two-camera system considered in this paper are arranged so that there is a small intersection of the fields of view. This configuration of divergent view improves the accuracy of the structure and motion estimation because the ambiguity mentioned above decreases due to a large field of view. In this paper, a recursive algorithm is proposed for fast scene model reconstruction using a two-camera system of divergent view. Using inversely inferred stereo correspondences in the intersection of the fields of view is also proposed to remove degeneracy of scale factor determination and to acquire more accurate results from the information redundancy. The results of the experiments with long term real image sequences are presented to demonstrate the feasibility of the proposed system.

论文关键词:Structure from motion,Field of view,Motion,Stereo,Stereo correspondence,Scene reconstruction,Extended Kalman filter

论文评审过程:Received 7 March 2008, Revised 23 July 2009, Accepted 27 December 2009, Available online 11 January 2010.

论文官网地址:https://doi.org/10.1016/j.patcog.2009.12.015