Computer Vision: Three-Dimensional Data from ImagesThis book explores computer vision, describing the reconstruction of object surfaces and the analysis of distances between camera and objects. Fundamentals and algorithms are presented, including topics such as dynamic stereo analysis, shape from shading, photometric stereo analysis, and structural illumination. New research results in shape reconstruction and depth analysis are also included. |
Common terms and phrases
algorithm allows analysis angle application approach approximately assignment assumed assumption begin calculated calibration called camera changes Chapter color component considered constraint coordinate system coordinates corresponding curve defined depends depth derivatives described determined discussed disparity displacement distance edge epipolar equal equation example exist face factor field Figure function geometry given gradient gray value height holds illumination direction illustrates image irradiance image plane image point initial integrability intersection iteration known Lambertian length light light source linear measured method motion normal Note object surface optical flow orientations pair parallel parameters pixels position possible problem projection properties radiance reconstruction reflectance map representation represented respect rotation scalar scene sequence shape shown shows solution specified sphere step stereo straight line surface points technique tion transformation unique vector visible visual