Arithmetic coding for data compression
Communications of the ACM
Atomic Decomposition by Basis Pursuit
SIAM Journal on Scientific Computing
Introduction to data compression (2nd ed.)
Introduction to data compression (2nd ed.)
MiniMax Methods for Image Reconstruction
MiniMax Methods for Image Reconstruction
DCC '97 Proceedings of the Conference on Data Compression
Vision: A Computational Investigation into the Human Representation and Processing of Visual Information
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Analysis of multimodal sequences using geometric video representations
Signal Processing - Special section: Multimodal human-computer interfaces
Efficient image representation by anisotropic refinement in matching pursuit
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
Sparse signal reconstruction from limited data using FOCUSS: are-weighted minimum norm algorithm
IEEE Transactions on Signal Processing
On the use of a priori information for sparse signal approximations
IEEE Transactions on Signal Processing
Greed is good: algorithmic results for sparse approximation
IEEE Transactions on Information Theory
Motion-compensated 3-D subband coding of video
IEEE Transactions on Image Processing
Sparse geometric image representations with bandelets
IEEE Transactions on Image Processing
Low-rate and flexible image coding with redundant representations
IEEE Transactions on Image Processing
Directionlets: anisotropic multidirectional representation with separable filtering
IEEE Transactions on Image Processing
Probability estimation in arithmetic and adaptive-Huffman entropy coders
IEEE Transactions on Image Processing
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In recent years, works on geometric multidimensional signal representations have established a close relation with signal expansions on redundant dictionaries. For this purpose, matching pursuits (MP) have shown to be an interesting tool. Recently, most important limitations of MP have been underlined, and alternative algorithms like weighted-MP have been proposed. This work explores the use of weighted-MP as a new framework for motion-adaptive geometric video approximations. We study a novel algorithm to decompose video sequences in terms of few, salient video components that jointly represent the geometric and motion content of a scene. Experimental coding results on highly geometric content reflect how the proposed paradigm exploits spatio-temporal video geometry. Two-dimensional weighted-MP improves the representation compared to those based on 2-D MP. Furthermore, the extracted video components represent relevant visual structures with high saliency. In an example application, such components are effectively used as video descriptors for the joint audio-video analysis of multimedia sequences.