A Kalman Filter Approach to Direct Depth Estimation Incorporating Surface Structure

Authors:
Y. S. Hung;H. T. Ho
Affiliations:
The Univ. of Hong Kong, Hong Kong;The Univ. of Hong Kong, Hong Kong
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1999

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Abstract

The problem of depth-from-motion using a monocular image sequence is considered. A pixel-based model is developed for direct depth estimation within a Kalman filtering framework. A method is proposed for incorporating local surface structure into the Kalman filter. Experimental results are provided to illustrate the effect of structural information on depth estimation.