SIFT-based Stereo Matching to Compensate Occluded Regions and Remove False Matching for 3D Reconstruction

Abstract

Generally, algorithms for generating disparity maps can be

clssified into two categories: region-based method and

feature-based method. The main focus of this research is to

generate a disparity map with an accuracy depth

information for 3-dimensional reconstructing . Basically,

the region-based method and the feature-based method are

simultaneously included in the proposed algorithm, so that

the existing problems including false matching and

occlusion can be effectively solved. As a region-based

method, regions of false matching are extracted by the

proposed MMAD(Modified Mean of Absolute Differences)

algorithm which is a modification of the existing

MAD(Mean of Absolute Differences) algorithm. As a

feature-based method, the proposed method eliminates

false matching errors by calculating the vector with SIFT

and compensates the occluded regions by using a pair of

adjacent SIFT matching points, so that the errors are

reduced and the disparity map becomes more accurate.