Energy Minimization Methods in Computer Vision and Pattern Recognition by Daniel Cremers
Overthelastdecades,energyminimizationmethods havebecomeanestablished paradigm to resolve a variety of challenges in the ?elds of computer vision and pattern recognition. While traditional approaches to computer vision were often based on a heuristic sequence of processing steps and merely allowed very l- ited theoretical understanding of the respective methods, most state-of-the-art methods are nowadays based on the concept of computing solutions to a given problem by minimizing respective energies. This volume contains the papers presented at the 7th International Conf- ence on Energy Minimization Methods in Computer Vision and Pattern Rec- nition (EMMCVPR 2009), held at the University of Bonn, Germany, August 24-28, 2009. These papers demonstrate that energy minimization methods have become a mature ?eld of research spanning a broad range of areas from discrete graph theoretic approaches and Markov random ?elds to variational methods and partial di?erential equations. Application areas include image segmentation and tracking, shape optimization and registration, inpainting and image deno- ing, color and texture modeling, statistics and learning. Overall, we received 75 high-quality double-blind submissions. Based on the reviewer recommendations, 36paperswereselectedforpublication,18asoraland18asposterpresentations. Both oral and poster papers were attributed the same number of pages in the conference proceedings. Furthermore, we were delighted that three leading experts from the ?elds of computer vision and energy minimization, namely, Richard Hartley (C- berra, Australia), Joachim Weickert (Saarbruc .. ken, Germany) and Guillermo Sapiro(Minneapolis,USA)agreedtofurtherenrichtheconferencewithinspiring keynote lectures.-
Image Analysis
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Image Analysis and Recognition
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Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008
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Computer Vision - ECCV 2020
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Pattern Recognition
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Information Processing in Computer-Assisted Interventions
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Biomedical Image Registration
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Computer Vision -- ACCV 2009
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Camera-Based Document Analysis and Recognition
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Modelling the Physiological Human
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Machine Learning in Medical Imaging
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Advances in Visual Computing
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Image and Video Technology -- PSIVT 2013 Workshops
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Computational Modeling of Objects Represented in Images
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Medical Image Computing and Computer-Assisted Intervention - MICCAI 2006
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Serious Games Development and Applications
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Geometric Science of Information
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Computer Vision – ECCV 2020
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Augmented Reality, Virtual Reality, and Computer Graphics
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Graph-Based Representations in Pattern Recognition
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Functional Imaging and Modeling of the Heart
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Scale Space and Variational Methods in Computer Vision
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Computational Forensics
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Computer Vision - ECCV 2018 Workshops
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Pattern Recognition and Artificial Intelligence
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Image and Video Technology
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Biometrics and Identity Management
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Computer Analysis of Images and Patterns
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Computer Vision - ECCV 2008
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Medical Biometrics
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Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges
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Computer Vision/Computer Graphics Collaboration Techniques
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Multiple Classifier Systems
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Image Analysis and Processing -- ICIAP 2011
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Progress in Pattern Recognition, Image Analysis and Applications
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Pattern Recognition and Image Analysis
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Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
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Computer Vision - ECCV 2018
| SKU | Unavailable |
| ISBN 13 | 9783642036408 |
| ISBN 10 | 3642036406 |
| Title | Energy Minimization Methods in Computer Vision and Pattern Recognition |
| Author | Daniel Cremers |
| Series | Image Processing Computer Vision Pattern Recognition And Graphics |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer |
| Year published | 2009-08-11 |
| Number of pages | 494 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |