Match!

Image Understanding Using Sparse Representations

Published on Apr 1, 2014
Jayaraman J. Thiagarajan14
Estimated H-index: 14
(LLNL: Lawrence Livermore National Laboratory),
Karthikeyan Natesan Ramamurthy14
Estimated H-index: 14
(IBM)
+ 1 AuthorsAndreas Spanias28
Estimated H-index: 28
Abstract
Image understanding has been playing an increasingly crucial role in several inverse problems and computer vision. Sparse models form an important component in image understanding, since they emulate the activity of neural receptors in the primary visual cortex of the human brain. Sparse methods have been utilized in several learning problems because of their ability to provide parsimonious, interpretable, and efficient models. Exploiting the sparsity of natural signals has led to advances in several application areas including image compression, denoising, inpainting, compressed sensing, blind source separation, super-resolution, and classification. The primary goal of this book is to present the theory and algorithmic considerations in using sparse models for image understanding and computer vision applications. To this end, algorithms for obtaining sparse representations and their performance guarantees are discussed in the initial chapters. Furthermore, approaches for designing overcomplete, data-adapted dictionaries to model natural images are described. The development of theory behind dictionary learning involves exploring its connection to unsupervised clustering and analyzing its generalization characteristics using principles from statistical learning theory. An exciting application area that has benefited extensively from the theory of sparse representations is compressed sensing of image and video data. Theory and algorithms pertinent to measurement design, recovery, and model-based compressed sensing are presented. The paradigm of sparse models, when suitably integrated with powerful machine learning frameworks, can lead to advances in computer vision applications such as object recognition, clustering, segmentation, and activity recognition. Frameworks that enhance the performance of sparse models in such applications by imposing constraints based on the prior discriminatory information and the underlying geometrical structure, and kernelizing the sparse coding and dictionary learning methods are presented. In addition to presenting theoretical fundamentals in sparse learning, this book provides a platform for interested readers to explore the vastly growing application domains of sparse representations.
  • References (127)
  • Citations (14)
References127
Newest
#1Karthikeyan Natesan Ramamurthy (ASU: Arizona State University)H-Index: 14
#2Jayaraman J. Thiagarajan (ASU: Arizona State University)H-Index: 14
Last.Andreas Spanias (ASU: Arizona State University)H-Index: 28
view all 3 authors...
#1Karthikeyan Natesan Ramamurthy (ASU: Arizona State University)H-Index: 14
#2Jayaraman J. Thiagarajan (ASU: Arizona State University)H-Index: 14
Last.Andreas Spanias (ASU: Arizona State University)H-Index: 28
view all 4 authors...
Nov 1, 2012 in BIBE (Bioinformatics and Bioengineering)
#1Jayaraman J. Thiagarajan (ASU: Arizona State University)H-Index: 14
#2Deepta Rajan (ASU: Arizona State University)H-Index: 4
Last.Andreas Spanias (ASU: Arizona State University)H-Index: 28
view all 5 authors...
Sep 1, 2012 in ICIP (International Conference on Image Processing)
#1Kuldeep Kulkarni (ASU: Arizona State University)H-Index: 7
#2Pavan Turaga (ASU: Arizona State University)H-Index: 24
Mar 1, 2012 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
#1Hien Nguyen (UMD: University of Maryland, College Park)H-Index: 16
#2Vishal M. Patel (UMD: University of Maryland, College Park)H-Index: 38
Last.Rama Chellappa (UMD: University of Maryland, College Park)H-Index: 93
view all 4 authors...
#1Jayaraman J. Thiagarajan (ASU: Arizona State University)H-Index: 14
#2Andreas Spanias (ASU: Arizona State University)H-Index: 28
Sep 1, 2011 in ICIP (International Conference on Image Processing)
#1Karthikeyan Natesan Ramamurthy (ASU: Arizona State University)H-Index: 14
#2Jayaraman J. Thiagarajan (ASU: Arizona State University)H-Index: 14
Last.Andreas Spanias (ASU: Arizona State University)H-Index: 28
view all 3 authors...
#1Jort F. Gemmeke (Radboud University Nijmegen)H-Index: 21
#2Tuomas Virtanen (TUT: Tampere University of Technology)H-Index: 41
Last.Antti Hurmalainen (TUT: Tampere University of Technology)H-Index: 11
view all 3 authors...
#1Jayaraman J. Thiagarajan (ASU: Arizona State University)H-Index: 14
#2Karthikeyan Natesan Ramamurthy (ASU: Arizona State University)H-Index: 14
Last.Andreas Spanias (ASU: Arizona State University)H-Index: 28
view all 3 authors...
Jun 1, 2011 in CVPR (Computer Vision and Pattern Recognition)
#1Roberto Rigamonti (EPFL: École Polytechnique Fédérale de Lausanne)H-Index: 7
#2Matthew Brown (EPFL: École Polytechnique Fédérale de Lausanne)H-Index: 23
Last.Vincent Lepetit (EPFL: École Polytechnique Fédérale de Lausanne)H-Index: 52
view all 3 authors...
Cited By14
Newest
May 1, 2019 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
#1Jayaraman J. Thiagarajan (LLNL: Lawrence Livermore National Laboratory)H-Index: 14
#2Rushil Anirudh (LLNL: Lawrence Livermore National Laboratory)H-Index: 6
Last.Peer-Timo Bremer (LLNL: Lawrence Livermore National Laboratory)H-Index: 26
view all 4 authors...
#1Huan Song (ASU: Arizona State University)H-Index: 4
#2Jayaraman J. Thiagarajan (LLNL: Lawrence Livermore National Laboratory)H-Index: 14
Last.Andreas Spanias (ASU: Arizona State University)H-Index: 28
view all 4 authors...
Nov 13, 2016 in HiPC (IEEE International Conference on High Performance Computing, Data, and Analytics)
#1Tanzima Islam (LLNL: Lawrence Livermore National Laboratory)H-Index: 6
#2Jayaraman J. Thiagarajan (LLNL: Lawrence Livermore National Laboratory)H-Index: 14
Last.Todd Gamblin (LLNL: Lawrence Livermore National Laboratory)H-Index: 17
view all 5 authors...
Sep 1, 2016 in ICIP (International Conference on Image Processing)
#1Huan Song (ASU: Arizona State University)H-Index: 4
#2Jayaraman J. Thiagarajan (LLNL: Lawrence Livermore National Laboratory)H-Index: 14
Last.Andreas Spanias (ASU: Arizona State University)H-Index: 28
view all 4 authors...
Mar 1, 2016 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
#1Huan Songg (ASU: Arizona State University)H-Index: 1
#2Jayaraman J. Thiagarajan (LLNL: Lawrence Livermore National Laboratory)H-Index: 14
Last.Pavan Turaga (ASU: Arizona State University)H-Index: 24
view all 5 authors...
View next paperSparse Representation Theory and Applications of Image:A Survey