000 02412nam a2200253 4500
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020 _a9780262015776
020 _a9780262298353
040 _aUniversiti Teknologi Brunei
_beng
100 1 _aBlake, Andrew.
_eauthor.
245 1 0 _aMarkov Random Fields for Vision and Image Processing
_cAndrew Blake, Pushmeet Kohli, Carsten Rother.
260 _aCambridge, Mass :
_bThe MIT Press.
_c2011.
500 _aThis book is automatically accessible within the University internet network. To learn how to access it outside the campus, visit: https://www.utb.edu.bn/media/cv5fcgwb/remote-access-for-ebscohost.pdf
520 _aState-of-the-art research on MRFs, successful MRF applications, and advanced topics for future study.This volume demonstrates the power of the Markov random field (MRF) in vision, treating the MRF both as a tool for modeling image data and, utilizing recently developed algorithms, as a means of making inferences about images. These inferences concern underlying image and scene structure as well as solutions to such problems as image reconstruction, image segmentation, 3D vision, and object labeling. It offers key findings and state-of-the-art research on both algorithms and applications.After an introduction to the fundamental concepts used in MRFs, the book reviews some of the main algorithms for performing inference with MRFs; presents successful applications of MRFs, including segmentation, super-resolution, and image restoration, along with a comparison of various optimization methods; discusses advanced algorithmic topics; addresses limitations of the strong locality assumptions in the MRFs discussed in earlier chapters; and showcases applications that use MRFs in more complex ways, as components in bigger systems or with multiterm energy functions. The book will be an essential guide to current research on these powerful mathematical tools.
650 4 _aMarkov random fields
650 4 _aComputer vision
_xMathematics
700 1 _eauhtor
_aKohli, Pushmeet.
700 1 _eauthor
_aRother,Carsten.
856 _uhttps://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=386846&site=ehost-live
942 _2lc
_cEBB
998 _eElectronic Book
_sReference No: 4736965 / 10.12.21 / ns277138 Date: 12 October 2021 -- (UTB) – EBSCO International, INC
999 _c21231
_d21231