Computer and Robot Vision, Volume 2This two-volume set is an authoritative, comprehensive, modern work on computer vision that covers all of the different areas of vision with a balance and unified approach. Volume II covers the higher level techniques of illumination, perspective projection, analytical photogrammetry, motion, image matching, consistent labeling, model matching, and knowledge based vision systems.Both volumes of Computer and Robot Vision address the growing and rapidly evolving area of computer vision with depth and breadth and explore details and specific algorithms not available in most competing texts. |
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3D line 3D point algorithm Analysis and Machine angle approximate assume b₁ b₂ camera coefficient components Computer Vision constraint corresponding cross-ratio defined depth error derived determined direction cosines edge estimate function geometric given gradient Haralick IEEE IEEE Transactions image plane image points Image Processing intersection iteration label least-squares lens line segment linear Machine Intelligence mapping matrix measure MF-estimator N-tuple node noise nonlinear normal equation object observed obtain optic flow orientation outliers P₁ pair parameters Pattern Analysis Pattern Recognition perspective projection Photogrammetry pixel position problem procedure projection plane reference frame relation represent rigid motion robust rotation rotation matrix sequence SNR(db solution solve spatial standard deviation stereo structure surface normal techniques three-dimensional Transactions on Pattern transformation translational two-dimensional u₁ u₂ uniquely unknown variance vector window x₁