Computer Vision: Three-Dimensional Data from Images
Springer Singapore, Sep 1, 1998 - Computers - 392 pages
This 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.
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Geometry of Object Surfaces
Static Stereo Analysis
6 other sections not shown
albedo algorithm angle approximately assignment assumed assumption BRDF calculated calibration object camera central projection color image compare Fig compare Section computer vision constraint coordinate system correspondence analysis curve defined described determined disparity map displacement vectors distance edge epipolar line equation example Figure focal length function given gradient map gradient space gray value height map illumination direction image acquisition image irradiance image plane image point integrability intersection irradiance image irradiance pair iteration Lambert's cosine law Lambertian reflectance Lambertian reflectance map left image light planes light source light stripe linear motion needle map object surface optical flow orthogonal parallel projection parameters photometric stereo pixels projection center radiance reflectance map representation right image rotation scalar disparity scene objects sensor SFS methods solid angle solution specified specular reflection standard stereo geometry straight line surface normal surface orientation surface points surface reconstruction technique Theorem three-dimensional tion transformation unique visual world coordinates