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Proceedings Paper

Sparse depth map reconstruction from image sequences of the buildings
Author(s): Zheng Hu; Min Sun
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Paper Abstract

This paper presents an improved cooperative matching algorithm based on feature regions. The proposed algorithm uses normal vector in each pixel position of the whole images to extract the feature regions of image sequences of buildings. In order to obtain a sparse depth map, matching areas are limited to feature regions rather than whole images. The image similarity of each pixel is defined as match value. Iteratively update match values and make the match values convergent. For each pixel, the pixel and disparity which the maximum match value corresponds to are regarded as matching results. By using feature regions extraction of image sequences, not only can the reconstruction process be further simplified, the running speed can also be increased. The experimental results show that our method is effective and can avoid mismatching in some regions which are texture-less or have sparse texture. Meanwhile, the problem of large computation is solved by pruning unnecessary matching regions.

Paper Details

Date Published: 30 October 2009
PDF: 7 pages
Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74981P (30 October 2009); doi: 10.1117/12.833932
Show Author Affiliations
Zheng Hu, Central South Univ. (China)
Min Sun, Peking Univ. (China)


Published in SPIE Proceedings Vol. 7498:
MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)

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