Trinocular Stereo: Theoretical Advantages and a New Algorithm

Charles V. Stewart

doi:10.1117/12.969992

1 March 1990 Trinocular Stereo: Theoretical Advantages and a New Algorithm

Charles V. Stewart

Proceedings Volume 1198, Sensor Fusion II: Human and Machine Strategies; (1990) https://doi.org/10.1117/12.969992
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States

Abstract

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.

Citation Download Citation

Charles V. Stewart "Trinocular Stereo: Theoretical Advantages and a New Algorithm", Proc. SPIE 1198, Sensor Fusion II: Human and Machine Strategies, (1 March 1990); https://doi.org/10.1117/12.969992

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available