Towards a fast and reliable dense matching algorithm

In this paper, we present a dense matching algorithm which utilizes the corner and edge features of images to increase the reliability and to speed up the process of dense matching of two uncalibrated images. The major problem of classical area-based dense matching algorithms is the high computational time resulting from intensive correlation calculations for match candidates. Although some methods have attempted to integrate image feature information in the dense matching of uncalibrated images, most of these methods are not practical and are difficult to implement. This paper aims at designing a hybrid matching algorithm that preserves disparity continuity at the object continuous surfaces while discontinuity at object boundaries are treated differently in the matching process. In particular, both CPU-time and likelyhood of mismatches are reduced while the implementation is kept simple and straightforward. keywords: dense matching, stereo vision