Trinocular Stereo: Theoretical Advantages and a New Algorithm

This paper presents a new three-camera stereo matching algorithm, called the Trinocular Local Matching Algorithm (TLMA), that helps to overcome some of the inherent problems in binocular matching. These problems include (1) the inability of binocular algorithms to obtain matches for horizontal edge segments, (2) secondary errors that arise in image regions containing unmatched horizontal segments, (3) the inability of binocular algorithms to obtain matches in occluded regions, (4) incorrect matches that may be accepted in occluded regions, and (5) the matching ambiguity of periodic image texture. TLMA matches images taken from cameras positioned on the vertices of an isosceles right triangle. Edges detected in the base image are matched with either the right or top image. For each candidate match a support value is computed using three support measures: the disparity gradient, the trinocular disparity gradient and cross-channel consistency multiresolution. Support values are compared for competing matches to determine the confidence in each match. High confidence matches that pass a final consistency check, called the area rule, are accepted as correct. TLMA is shown to avoid some of the design errors of previous trinocular algorithms. Preliminary experimental results on both real and synthetic images comparing TLMA with a similarly defined binocular algorithm demonstrate TLMA's effectiveness in producing improved matching results.