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Camera calibration is a key step in three-dimensional (3-D) reconstruction; however, the calibration accuracy and stability often suffer from complicated illumination in real applications. The camera calibration method using the checkerboard pattern is improved for high-precision calibration under complicated illumination. First, an improved Harris corner detector based on color constancy, as well as a subpixel optimization method based on prior knowledge of the checkerboard, are proposed to overcome the influence of bad lighting. Second, a checkerboard pattern with a central circle point is designed for better reference point location for uneven illumination. The checkerboard identification by Delaunay triangulation is also improved for the situation of discontinuity caused by over-saturation. Finally, the camera parameter optimization process is improved to reduce the calibration error produced by complicated illumination. Experimental results show that the improvements achieve more accurate and stable calibration results in complicated lighting conditions compared with traditional methods. ©2018 SPIE and IS&T[DOI: 10.1117/1.JEI.27.4.043038] [ABSTRACT FROM AUTHOR]

Texture information plays an important role in rendering true objects, especially with the wide application of image-based three-dimensional (3-D) reconstruction and 3-D laser scanning. This paper proposes a seamless texture mapping algorithm to achieve a high-quality visual effect for 3-D reconstruction. At first, a series of image sets is produced by analyzing the visibility of triangular facets, the image sets are clustered and segmented into a number of optimal reference texture patches. Second, the generated texture patches are sequenced to create a rough texture map, then a weighting process is adopted to reduce the color discrepancies between adjacent patches. Finally, a multiresolution decomposition and fusion technique is used to generate the transition section and eliminate the boundary effect. Experiments show that the proposed algorithm is effective and practical for obtaining high-quality 3-D texture mapping for 3-D reconstruction. Compared with traditional methods, it maintains the texture clarity while eliminating the color seams, in addition, it also supports 3-D texture mapping for big data application. © 2016 SPIE and IS&T [DOI: 10.1117/1.JEI.25.5.053025] [ABSTRACT FROM AUTHOR]