Computer Vision Research Progress
Computer vision is the science and technology of machines that see. As a scientific discipline, computer vision is concerned with the theory and technology for building artificial systems that obtain information from images. The image data can take many forms, such as a video sequence, views from multiple cameras, or multi-dimensional data from a medical scanner. As a technological discipline, computer vision seeks to apply the theories and models of computer vision to the construction of computer vision systems. Examples of applications of computer vision systems include systems for controlling processes (e.g. an industrial robot or an autonomous vehicle). Detecting events (e.g. for visual surveillance). Organizing information (e.g. for indexing databases of images and image sequences), Modeling objects or environments (e.g. industrial inspection, medical image analysis or topographical modeling), Interaction (e.g. as the input to a device for computer-human interaction). Computer vision can also be described as a complement (but not necessarily the opposite) of biological vision. In biological vision, the visual perception of humans and various animals are studied, resulting in models of how these systems operate in terms of physiological processes. Computer vision, on the other hand, studies and describes artificial vision system that are implemented in software and/or hardware. Interdisciplinary exchange between biological and computer vision has proven increasingly fruitful for both fields. Sub-domains of computer vision include scene reconstruction, event detection, tracking, object recognition, learning, indexing, ego-motion and image restoration. This new book presents leading-edge new research from around the world.
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A FOLLOWUP OF IMAGE REGISTRATION TECHNIQUES FOR APPLICATION IN DIGITAL SUBTRACTION ANGIOGRAPHY
INTELLIGENT VIDEO ANALYSIS FOR TRAFFIC SURVEILLANCE BY PERCEPTUAL EDGE FEATURE GROUPING
ACCURATELY CALIBRATING THE IMAGE DISTORTION CENTERS OF RADIAL CAMERAS
TWIN OBJECTCENTERED MODELS FOR 3D RECONSTRUCTION
FAST FACE DETECTOR AND RECOGNITION FOR BIOMETRICAL SECURITY SYSTEMS
JOINT ROTATION SHIFT AND SCALE INVARIANT FEATURE EXTRACTION FOR CONTENTBASED IMAGE RETRIEVAL
APPLICATION OF COMPUTER VISION IN SHORTEST PATH PLANNING
OBJECT DETECTION AND TRACKING USING BAYESCONSTRAINED PARTICLE SWARM OPTIMIZATION
HEAD POSE ESTIMATION AND MULTIVIEW FACE RECOGNITION WITH NONLINEAR DIMENSIONALITY REDUCTION METHODS
EVIDENCEBASED PIXEL LABELING FOR COLOR IMAGE SEGMENTATION
EQUALITY FOR MANUFACTURING EQM USING INTERNETBASED COMPUTER VISION SYSTEM
EVALUATION AND ASSESSMENT OF RIGID AFFINE AND NONRIGID REGISTRATION TECHNIQUES APPLICATION TO XRAY ANGIOGR...
analysis application approach calibration catadioptric Computer Vision contour contrast image control points coordinates corresponding dandelion model dataset defined deformation digital subtraction angiography distance transformation distortion image doubt degree DSA images edge energy signatures equation error Euclidean distance face recognition feature extraction feature vector frame function geometric global identification IEEE IEEE Trans image distortion center image points Image Processing image rectification image registration image retrieval image sequence invariant wavelet Isomap iteration step labeled mask image method MGET graph moire motion artifacts movement points normalized polar obtained optimization parameters Particle Swarm Optimization patient motion Pattern Recognition pentahedron perceptual performed pixels pose estimation problem projective proposed radial camera reconstruction region registration techniques robot rotation row shift scale invariant SCV model segmentation shift and scale shown in Figure silhouette space points structure surface target texture tracking transformation twin models values visual hull voxel wavelet packet