Real-time stereo on GPGPU using progressive multi-resolution adaptive windows
Real-time stereo on GPGPU using progressive multi-resolution adaptive windows
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DOI：
10.1016/j.imavis.2011.01.007
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发表时间：
2011-05-01
影响因子：
4.7
通讯作者：
Taubin, Gabriel
中科院分区：
文献类型：
--
作者：
Zhao, Yong;Taubin, Gabriel
提出了一种基于GPGPU的实时密集立体匹配算法。该算法基于一个渐进的多分辨率流水线，包括背景建模和自适应窗口的密集匹配。对于只关注运动物体的应用，该方法有效地降低了整体计算成本，并保留了高清晰度的细节。在现成的商品图形卡上运行，我们的实现在1024 x 768立体视频上实现了36 fps的立体匹配，具有精细的256像素视差范围。这实际上与每秒7200 M视差评估相同。对于静态背景假设的场景，我们的方法在速度性能方面优于所有已发布的替代算法，大幅度提高。我们设想了一些潜在的应用，如实时运动捕捉，以及跟踪，识别和多摄像机网络中的移动对象的识别。(C)2011 Elsevier B.V.保留所有权利。
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 x 768 stereo video with a fine 256 pixel 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. (C) 2011 Elsevier B.V. All rights reserved.