Variational Geometric And Level Set Methods In Computer Vision
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Variational, Geometric, and Level Set Methods in Computer Vision
Mathematical methods has been a dominant research path in computational vision leading to a number of areas like ?ltering, segmentation, motion analysis and stereo reconstruction. Within such a branch visual perception tasks can either be addressed through the introduction of application-driven geometric ?ows or through the minimization of problem-driven cost functions where their lowest potential corresponds to image understanding. The 3rd IEEE Workshop on Variational, Geometric and Level Set Methods focused on these novel mathematical techniques and their applications to c- puter vision problems. To this end, from a substantial number of submissions, 30 high-quality papers were selected after a fully blind review process covering a large spectrum of computer-aided visual understanding of the environment. The papers are organized into four thematic areas: (i) Image Filtering and Reconstruction, (ii) Segmentation and Grouping, (iii) Registration and Motion Analysis and (iiii) 3D and Reconstruction. In the ?rst area solutions to image enhancement, inpainting and compression are presented, while more advanced applications like model-free and model-based segmentation are presented in the segmentation area. Registration of curves and images as well as multi-frame segmentation and tracking are part of the motion understanding track, while - troducing computationalprocessesinmanifolds,shapefromshading,calibration and stereo reconstruction are part of the 3D track. We hope that the material presented in the proceedings exceeds your exp- tations and will in?uence your research directions in the future. We would like to acknowledge the support of the Imaging and Visualization Department of Siemens Corporate Research for sponsoring the Best Student Paper Award.
Geometric Level Set Methods in Imaging, Vision, and Graphics
Author: Stanley Osher
language: en
Publisher: Springer Science & Business Media
Release Date: 2003-07-17
Here is, for the first time, a book that clearly explains and applies new level set methods to problems and applications in computer vision, graphics, and imaging. It is an essential compilation of survey chapters from the leading researchers in the field. The applications of the methods are emphasized.
Geometric Level Set Methods in Imaging, Vision, and Graphics
Author: Stanley Osher
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-05-08
Introduction Imageprocessing,computervisionandcomputergraphicsarenowestablished - search areas. Pattern recognition and arti?cial intelligence were the origins of the explorationofthespace ofimages.Simplistic digitaltechniquesusedatthe beg- ning of 60’s for gray image processing operations have been now replaced with a complex mathematical framework that aims to exploit and understand images in two and three dimensions. Advances in computing power continue to make the use and processing of visual information an important part of our lives. The evolution of these techniques was a natural outcome of the need to p- cess an emerging informationspace, the space of natural images. Images in space and time are now a critical part of many human activities. First, pictures and now video streams were used to eternalize small and signi?cant moments of our life. Entertainment including movies, TV-programs and video games are part of our every-day life where capturing, editing, understanding and transmitting images are issues to be dealt with. The medical sector is also a major area for the use of images. The evolution of the acquisition devices led to new ways of capturing information, not visible by the human eye. Medical imaging is probably the most established market for processing visual information[405]. Visualization of c- plex structures and automated processing towards computer aided diagnosis is used more and more by the physicians in the diagnostic process. Safety and se- rity are also important areas where images and video play a signi?cant role [432].