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Slabaugh, G.G.; Basaru, R. R.; Child, C. H. T.; Alonso, E.
Languages: English
Types: Unknown
Subjects: Q1, T1

Classified by OpenAIRE into

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.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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    • [15] Xin Luan, Honghong Zhou, Fangjie Yu, Xiufang Li, Bing Xue, and Dalei Song: A robust Local Census-based Stereo matching insensitive to Illumination changes, Proc. of International conference on Information and Automation (ICIA), 2012.
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    • [17] “Siddhant Ahuja's webpage” [Accessed 9th June 2014] Available: http://siddhantahuja.wordpress.com/
  • No related research data.
  • Discovered through pilot similarity algorithms. Send us your feedback.

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