Local Surface Structure From Disparity Measurements

Michael R. M. Jenkin; Allan D. Jepson; John K. Tsotsos

doi:10.1117/12.942870

12 March 1988 Local Surface Structure From Disparity Measurements

Michael R. M. Jenkin, Allan D. Jepson, John K. Tsotsos

Proceedings Volume 0850, Optics, Illumination, and Image Sensing for Machine Vision II; (1988) https://doi.org/10.1117/12.942870
Event: Advances in Intelligent Robotics Systems, 1987, Cambridge, CA, United States

Abstract

Current theories of stereopsis involve three distinct stages: First, the two images of a stereo pair are processed separately to extract monocular features. One common choice of feature is the presence of a zero-crossing in a bandpassed versions of the image. Second, the monocular features in one image are matched with corresponding features found in the other image. In practice this second stage cannot be expected to produce only the correct matches, and a third stage must be considered in order to remove the incorrect matches ("false targets"). There are therefore three main issues the design of such a traditional algorithm for stereopsis, namely i) the choice of image features; the choice of matching criteria; and iii) the way false targets are avoided or eliminated. In this paper we introduce a different approach. We propose that symbolic features should not be extracted from the monocular images in the first stage of processing. Rather we examine a technique for measuring the local phase difference between the two images. We show how local phase difference in a bandpassed version of the image can be interpreted as disparity. This essentially combines the first two stages of the traditional approach. These disparity measurements may contain "false targets" which must be eliminated. Building upon the results of these disparty detectors, we show that a simple surface model based on object cohesiveness and local surface planarity across a range of spatial-frequency tuned channels can be used to reduce false matches. The resulting local planar surface support can be used to segment the image into planar regions in depth. Due to the independent nature of both the disparity detection and local planar support mechanism, this method is capable of dealing with both opaque and transparent stimuli.

Citation Download Citation

Michael R. M. Jenkin, Allan D. Jepson, and John K. Tsotsos "Local Surface Structure From Disparity Measurements", Proc. SPIE 0850, Optics, Illumination, and Image Sensing for Machine Vision II, (12 March 1988); https://doi.org/10.1117/12.942870

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