Adaptive area-based stereo matching

Christian Menard; Robert Sablatnig

doi:10.1117/12.302449

6 March 1998 Adaptive area-based stereo matching

Christian Menard, Robert Sablatnig

Proceedings Volume 3313, Three-Dimensional Image Capture and Applications; (1998) https://doi.org/10.1117/12.302449
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States

Abstract

The stereo analysis method is similar to the human visual system. Due to the way our eyes are positioned and controlled, our brains usually receive similar images of a scene taken from nearby points of the same horizontal level. Stereo tries to imitate this principle by computing the distance of objects, 'their depth,' from two images of two cameras using the triangulation principle. Points of imaged objects are mapped in different locations in the two stereo images. These points need to be identified in both images. The correspondences are established by correlating windows of the left and right image and finding a maximum. A central problem in stereo matching using correlation techniques lies in selecting the size of the search window. Small windows contain only a small number of data points, and thus are very sensitive to noise and therefore result in false matches. Whereas large search windows contain data from two or more different objects or surfaces, thus the estimated disparity is not accurate due to different projective distortions in the left and the right image. The new method introduces a continuous scale parameter for the matching process. It allows the adaption of the scale for every individual region and overcomes the drawbacks of fixed window sizes which is impressively demonstrated by the experimental results.

Citation Download Citation

Christian Menard and Robert Sablatnig "Adaptive area-based stereo matching", Proc. SPIE 3313, Three-Dimensional Image Capture and Applications, (6 March 1998); https://doi.org/10.1117/12.302449

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