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Quantized Census for Stereoscopic Image Matching

Slabaugh, G. G., Basaru, R. R., Child, C. H. T. & Alonso, E. (2015). Quantized Census for Stereoscopic Image Matching. Paper presented at the Second International Conference on 3D Vision (3DV 2014), 08-12-2014 - 11-12-2014, Tokyo, Japan.


Current depth capturing devices show serious drawbacks in certain applications, for example ego-centric depth recovery: they are cumbersome, have a high power requirement, and do not portray high resolution at near distance. Stereo-matching techniques are a suitable alternative, but whilst the idea behind these techniques is simple it is well known that recovery of an accurate disparity map by stereo-matching requires overcoming three main problems: occluded regions causing absence of corresponding pixels; existence of noise in the image capturing sensor and inconsistent color and brightness in the captured images. We propose a modified version of the Census-Hamming cost function which allows more robust matching with an emphasis on improving performance under radiometric variations of the input images.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Subjects: Q Science > Q Science (General)
T Technology > T Technology (General)
Departments: School of Science & Technology > Computer Science
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