Abstract
3D reconstruction based on high-level features, such as line and plane, is a significant development trend in Digital Photogrammetry and Computer Vision. To auto-recognize corresponding line and point is a core problem in above research areas. Therefore this article presents a novel line segment stereo recognition algorithm based on straight line auto-grouping, epipolar line constraint guiding, vanishing point direction guiding, and image pyramid model. The strategy for auto-recognizing corresponding line bases on “independent observation” + “local integral constraint” + “large area search” + “probability relaxation”, so our algorithm satisfies objective law that the global distribution of space-object is discontinuous but local is continuous. Simultaneously, in order to overcome image geometric distortion, NCC similarity measure based on SIFT operator compensating is presented. Furthermore, in corresponding line recognition, the problems of discontinuties in space and variation of parallax can be solved. Finally, through comparing with method of homography line matching, experimental results prove that our algorithm has a better reliability, rightness and precision. Moreover this research paves the way for auto-3D-reconstruction.
Sponsored by the Key Program of Ministry of Education (No.108098) and the National Natural Science Foundation of China (No.40671078).
Civil Defense Industry Special Scientific Research Project (Objects / environmental electromagnetic sources of Theoretical and Key Technology Research).
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Li, C., Liu, P., Zhou, Y. (2012). A Strategy on Corresponding Line Segment Recognition for 3D-Reconstruction. In: Deng, W. (eds) Future Control and Automation. Lecture Notes in Electrical Engineering, vol 172. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31006-5_10
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DOI: https://doi.org/10.1007/978-3-642-31006-5_10
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