A novel algorithm for disparity/depth estimation from multi-view images is presented. A dynamic programming approach with window-based correlation and a novel cost function is proposed. The smoothness of disparity/depth map is embedded in dynamic programming approach, whilst the window-based correlation increases reliability. The enhancement methods are included, i.e. adaptive window size and shiftable window are used to increase reliability in homogenous areas and to increase sharpness at object boundaries. First, the algorithms estimate depth maps along a single camera axis. The algorithms exploits then combines the depth estimates from different axis to derive a suitable depth map for multi-view images. The proposed scheme outperforms existing approaches in parallel and in the non-parallel camera configurations
|Translated title of the contribution
|Dynamic programming for multi-view disparity/depth estimation
|Title of host publication
|2006 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006) Toulouse, France
|Institute of Electrical and Electronics Engineers (IEEE)
|269 - 272
|Number of pages
|Published - May 2006
|2006 IEEE International Conference on Acoustics, Speech and Signal Processing - Centre de Congrès Pierre Baudis, Toulouse, France
Duration: 14 May 2006 → 19 May 2006
|2006 IEEE International Conference on Acoustics, Speech and Signal Processing
|14/05/06 → 19/05/06
Bibliographical noteRose publication type: Conference contribution
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