`Region-growing' algorithm for matching of terrain images
Image and Vision Computing
Practical approach to the stereo matching of urban imagery
Image and Vision Computing
Detection and Modeling of Buildings from Multiple Aerial Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Finding the Largest Unambiguous Component of Stereo Matching
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
SMBV '01 Proceedings of the IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV'01)
Advances in Computational Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
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This paper presents a new stereo matching algorithm based on region growing algorithm. To avoid visiting the entire disparity space, an algorithm has been proposed that greedily grow the corresponding patches from a given set of reliable seed correspondences. The proposed algorithm is using regions as matching primitives and defines the corresponding region energy functional for matching by utilising matching technique. Initially, a pre-matching technique i.e., Harris corner detector is used to obtain the initial matching points called, seed points. Secondly, a local window-based matching method is used to determine the disparity estimate from an initial set of seeds. Finally mode filter technique fills the gap of insufficiency of the sparse disparity for whole surface reconstruction. The results show that the proposed scheme is reliable, accurate and robust to high resolution aerial images. The proposed approach is very useful in 3D city model as buildings are the most important objects in producing a 3D city model.