Real-Time Stereo on GPGPU using Progressive Multi-Resolution Adaptive Windows

Yong Zhao, Gabriel Taubin
Division of Engineering, Brown University. 182 Hope Street, Providence, RI 02912, United States
Image and Vision Computing (16 February 2011)


   title={Real-Time Stereo on GPGPU using Progressive Multi-Resolution Adaptive Windows},

   author={Zhao, Y. and Taubin, G.},

   journal={Image and Vision Computing},





Source Source   



We introduce a new GPGPU-based real-time dense stereo matching algorithm. The algorithm is based on a progressive multi-resolution pipeline which includes background modeling and dense matching with adaptive windows. For applications in which only moving objects are of interest, this approach effectively reduces the overall computation cost quite significantly, and preserves the high definition details. Running on an off-the-shelf commodity graphics card, our implementation achieves a 36 fps stereo matching on 1024×768 stereo video with a fine 256 pixels disparity range. This is effectively same as 7200 M disparity evaluations per second. For scenes where the static background assumption holds, our approach outperforms all published alternative algorithms in terms of the speed performance, by a large margin. We envision a number of potential applications such as real-time motion capture, as well as tracking, recognition and identification of moving objects in multi-camera networks.
No votes yet.
Please wait...

* * *

* * *

HGPU group © 2010-2021 hgpu.org

All rights belong to the respective authors

Contact us: