TY - BOOK ID - 209806 TI - Handbook of mathematical models in computer vision AU - Paragios, Nikos. AU - Chen, Yunmei. AU - Faugeras, Olivier PY - 2006 SN - 1280612185 9786610612185 0387288317 0387263713 1441938850 9780387263717 9780387288314 PB - New York : Springer, DB - UniCat KW - Computer vision KW - Mathematical models KW - Machine vision KW - Vision, Computer KW - Artificial intelligence KW - Image processing KW - Pattern recognition systems KW - Computer simulation. KW - Computer vision. KW - Computer science. KW - Simulation and Modeling. KW - Mathematical Modeling and Industrial Mathematics. KW - Computer Imaging, Vision, Pattern Recognition and Graphics. KW - Math Applications in Computer Science. KW - Informatics KW - Science KW - Computer modeling KW - Computer models KW - Modeling, Computer KW - Models, Computer KW - Simulation, Computer KW - Electromechanical analogies KW - Simulation methods KW - Model-integrated computing KW - 681.3*I54 KW - 681.3*I54 Applications: computer vision; signal processing; text processing; waveform analysis (Pattern recognition) KW - Applications: computer vision; signal processing; text processing; waveform analysis (Pattern recognition) KW - Mathematical models. KW - Optical data processing. KW - Computer science—Mathematics. KW - Optical computing KW - Visual data processing KW - Bionics KW - Electronic data processing KW - Integrated optics KW - Photonics KW - Computers KW - Models, Mathematical KW - Optical equipment UR - https://www.unicat.be/uniCat?func=search&query=sysid:209806 AB - Visual perception refers to the ability of understanding the visual information that is provided by the environment. Such a mechanism integrates several human abilities and was studied by many researchers with different scientific origins including philosophy, physiology, biology, neurobiology, mathematics and engineering. In particular in the recent years an effort to understand, formalize and finally reproduce mechanical visual perception systems able to see and understand the environment using computational theories was made by mathematicians, statisticians and engineers. Such a task connects visual tasks with optimization processes and the answer to the visual perception task corresponds to the lowest potential of a task-driven objective function. In this edited volume we present the most prominent mathematical models that are considered in computational vision. To this end, tasks of increasing complexity are considered and we present the state-of-the-art methods to cope with such tasks. The volume consists of six thematic areas that provide answers to the most dominant questions of computational vision: Image reconstruction, Segmentation and object extraction, Shape modeling and registration, Motion analysis and tracking, 3D from images, geometry and reconstruction Applications in medical image analysis. ER -