April 1, 1993IEEE Transactions on Pattern Analysis and Machine Intelligence943 citations
View Full PaperA multiple-baseline stereo
Key Points
- The aim is to develop a stereo matching method that accurately estimates distances using multiple stereo pairs to eliminate ambiguity.
- Utilized a stereo matching algorithm based on the sum of squared differences (SSD) function.
- Introduced the SSSD-in-inverse-distance function to improve distance estimation precision.
- Conducted experiments with real stereo images to validate the effectiveness of the proposed method.
- The SSSD-in-inverse-distance function achieved a distinct minimum at the correct matching position.
- Experimental results indicated marked improvement in distance estimation accuracy in complex scenes with ambiguous patterns.
Abstract
A stereo matching method that uses multiple stereo pairs with various baselines generated by a lateral displacement of a camera to obtain precise distance estimates without suffering from ambiguity is presented. Matching is performed simply by computing the sum of squared-difference (SSD) values. The SSD functions for individual stereo pairs are represented with respect to the inverse distance and are then added to produce the sum of SSDs. This resulting function is called the SSSD-in-inverse-distance. It is shown that the SSSD-in-inverse-distance function exhibits a unique and clear minimum at the correct matching position, even when the underlying intensity patterns of the scene include ambiguities or repetitive patterns. The authors first define a stereo algorithm based on the SSSD-in-inverse-distance and present a mathematical analysis to show how the algorithm can remove ambiguity and increase precision. Experimental results with real stereo images are presented to demonstrate the effectiveness of the algorithm.>