16 December 1988 Neural Network Approach To Stereo Matching
Author Affiliations +
A method for matching stereo images using a neural network is presented. We first fit a polynomial to find a smooth continuous intensity function in a window and estimate the first order intensity derivatives. Combination of smoothing and differentiation results in a window operator which functions very similar to the human eye in detecting the intensity changes. Since natural stereo images are usually digitized for the implementation on a digital computer, we consider the effect of spatial quantization on the estimation of the derivatives from natural images. A neural network is then employed for matching the estimated first order derivatives under the epipolar, photometric and smoothness constraints. Owing to the dense intensity derivatives a dense array of disparities is generated with only a few iterations. This method does not require surface interpolation. Experimental results using natural images pairs are presented to demonstrate the efficacy of our method.
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Y. T. Zhou, Y. T. Zhou, R. Chellappa, R. Chellappa, } "Neural Network Approach To Stereo Matching", Proc. SPIE 0974, Applications of Digital Image Processing XI, (16 December 1988); doi: 10.1117/12.948464; https://doi.org/10.1117/12.948464

Back to Top