Real-Time Spatiotemporal Stereo Matching Using the Dual-Cross-Bilateral Grid

  • Christian Richardt
  • Douglas Orr
  • Ian Davies
  • Antonio Criminisi
  • Neil A. Dodgson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6313)


We introduce a real-time stereo matching technique based on a reformulation of Yoon and Kweon’s adaptive support weights algorithm [1]. Our implementation uses the bilateral grid to achieve a speedup of 200× compared to a straightforward full-kernel GPU implementation, making it the fastest technique on the Middlebury website. We introduce a colour component into our greyscale approach to recover precision and increase discriminability. Using our implementation, we speed up spatial-depth superresolution 100×. We further present a spatiotemporal stereo matching approach based on our technique that incorporates temporal evidence in real time (> 14 fps). Our technique visibly reduces flickering and outperforms per-frame approaches in the presence of image noise. We have created five synthetic stereo videos, with ground truth disparity maps, to quantitatively evaluate depth estimation from stereo video. Source code and datasets are available on our project website.


Stereo Match Cost Aggregation CIELAB Colour Space Stereo Video Support Window 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Supplementary material

978-3-642-15558-1_37_MOESM1_ESM.avi (5.9 mb)
Electronic Supplementary Material (6,085 KB)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Christian Richardt
    • 1
  • Douglas Orr
    • 1
  • Ian Davies
    • 1
  • Antonio Criminisi
    • 2
  • Neil A. Dodgson
    • 1
  1. 1.University of Cambridge, United Kingdom 
  2. 2.Microsoft Research CambridgeUnited Kingdom

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