Calculating dense disparity maps from color stereo images, an efficient implementation
Calculating dense disparity maps from color stereo images, an efficient implementation
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DOI：
10.1023/a:1014581421794
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发表时间：
2002-04-01
影响因子：
19.5
通讯作者：
Männer, R
中科院分区：
文献类型：
--
作者：
Mühlmann, K;Maier, D;Männer, R
本文提出了一种基于相关立体的有效实现方法。该领域的研究大致可以分为两类：不考虑计算时间的提高精度和实时场景重建。实现视频帧率的算法必须在图像大小和视差搜索范围上有很强的限制，而高质量的结果通常需要每对图像几分钟。本文试图填补这一空白，它提供了如何以高速和合理的质量实现基于相关的视差计算的指导，可以用于广泛的应用，或者为更复杂的方法提供一个初步的解决方案。从左到右一致性检查和唯一性验证用于消除错误匹配。可选地，可以对结果应用快速中值过滤器以进一步去除异常值。源代码将作为对开源计算机视觉库的贡献公开提供，计划在不久的将来使用SIMD指令进一步加速。
This paper presents an efficient implementation for correlation based stereo. Research in this area can roughly be divided in two classes: improving accuracy regardless of computing time and scene reconstruction in real-time. Algorithms achieving video frame rates must have strong limitations in image size and disparity search range, whereas high quality results often need several minutes per image pair. This paper tries to fill the gap, it provides instructions how to implement correlation based disparity calculation with high speed and reasonable quality that can be used in a wide range of applications or to provide an initial solution for more sophisticated methods. Left to right consistency checking and uniqueness validation are used to eliminate false matches. Optionally, a fast median filter can be applied to the results to further remove outliers. Source code will be made publicly available as contribution to the Open Source Computer Vision Library, further acceleration with SIMD instructions is planned for the near future.