Date of Award

8-1-2013

Degree Name

Master of Science

Department

Computer Science

First Advisor

CHENG, QIANG

Abstract

In this thesis, a novel and fast method to compute the dense disparity map of a stereo pair of images is presented. Most of the current stereo matching algorithms are ill suited for real-time matching owing to their time complexity. Methods that concentrate on providing a real-time performance, sacrifice much in accuracy. The presented method, Fast Estimation of Dense Disparity Map Using Pivot Points (FEDDUP), uses a hierarchical approach towards reduction of search space to find the correspondences. The hierarchy starts with a set of points and then it moves on to a mesh with which the edge pixels are matched. This results in a semi-global disparity map. The semi global disparity map is then used as a soft constraint to find the correspondences of the remaining points. This process delivers good real-time performance with promising accuracy.

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