Research On Dense 3D Reconstruction Method Based On Mesh Candidates

Stereo vision is one of the most important non-contact measurement techniques which acquire depth information from 2-D images. The 3-D contour of the object or scene can be reconstructed by corresponding point matching. The stereo vision technique was widely applied in many fields such as industrial inspection, reverse engineering, aerial mapping, medical imaging, robot navigation, etc. With stereo-vision-based dense reconstruction of the scene, the autonomous mobile robots have information exchange with the environment. How to improve the efficient of the 3D reconstruction is the key problem for the real-time requirement of the robot navigation, especially in the unstructured unknown environment. Aiming at the computational cost problem, the dense matching algorithm based on mesh candidate was proposed, and the graph cut was used for global optimization. The specific tasks include:A new 3D measurement method based on the mesh candidates was proposed. The depth can be recovered according to the region correlation of the correspondences. With depth candidates, the stereo correspondence was simplified from the 2D search problem to 1D search problem. The epipolar rectification of the images and the calculation of the 3D coordinate were no longer needed. The node coordinates in depth direction was determined by sup-pixel coordinates of the corresponding point in the reference image, which ensure the reasonable of the nodes distribution.According to the problem of the matching cost about large amount of the candidates in dense reconstruction, the pyramidal decomposition of the image was conducted using 2D discrete wavelet transform. The corresponding relationship between the nodes in different resolutions and decomposed images must be determined. By candidate screening from coarse to fine, the computational efficiency of dense matching can be improved. The binocular stereo vision system was represented by the trinocular one. If the confidence coefficient of the correlation curves is less than the preset threshold, the candidates of potential ambiguity can be reconsidered by another correspondence pair, by which the matching ambiguity was eliminated. In the circumstance with unsatisfactory light or the surface short of texture, the structured light was used to increase artificial texture. Based on the distribution of the corresponding points, the multi-block sawtooth pattern was designed for aided measurement. The precision of the 3D reconstruction improved by structured light in specific circumstance.By research on the relationship between mesh nodes and the graph, the graph can be established using nodes in world coordinate system. The global optimization of the dense 3D reconstruction would be fulfilled by minimization of the energy function, which solved the problem of the matching precision in low-texture region and discontinuous region. The simplified graph was constructed by screened nodes, and the energy function could be set by pre-calculated normalized cross correlation value. The algorithm complexity was decreased with a small quantity of the nodes. The accuracy and efficiency were verified by experimental result.The dense 3D reconstruction method based on mesh candidate simplified the computational complexity of the correspondence problem, expanding the application in the area of environmental awareness of the autonomous mobile robot. The performance of the dense reconstruction of the 3D scene was verified by experiments.