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Displaying 1-16 out of 16 total
Group action induced distances for averaging and clustering Linear Dynamical Systems with applications to the analysis of dynamic scenes
Found in: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
By B. Afsari,R. Chaudhry,A. Ravichandran,R. Vidal
Issue Date:June 2012
pp. 2208-2215
We introduce a framework for defining a distance on the (non-Euclidean) space of Linear Dynamical Systems (LDSs). The proposed distance is induced by the action of the group of orthogonal matrices on the space of statespace realizations of LDSs. This dista...
 
Robust classification using structured sparse representation
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By E. Elhamifar,R. Vidal
Issue Date:June 2011
pp. 1873-1879
In many problems in computer vision, data in multiple classes lie in multiple low-dimensional subspaces of a high-dimensional ambient space. However, most of the existing classification methods do not explicitly take this structure into account. In this pa...
 
Distributed computer vision algorithms through distributed averaging
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By R. Tron,R. Vidal
Issue Date:June 2011
pp. 57-63
Traditional computer vision and machine learning algorithms have been largely studied in a centralized setting, where all the processing is performed at a single central location. However, a distributed approach might be more appropriate when a network wit...
 
Categorizing Dynamic Textures Using a Bag of Dynamical Systems
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By A. Ravichandran,R. Chaudhry,R. Vidal
Issue Date:February 2013
pp. 342-353
We consider the problem of categorizing video sequences of dynamic textures, i.e., nonrigid dynamical objects such as fire, water, steam, flags, etc. This problem is extremely challenging because the shape and appearance of a dynamic texture continuously c...
 
See all by looking at a few: Sparse modeling for finding representative objects
Found in: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
By E. Elhamifar,G. Sapiro,R. Vidal
Issue Date:June 2012
pp. 1600-1607
We consider the problem of finding a few representatives for a dataset, i.e., a subset of data points that efficiently describes the entire dataset. We assume that each data point can be expressed as a linear combination of the representatives and formulat...
 
A closed form solution to robust subspace estimation and clustering
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By P. Favaro,R. Vidal,A. Ravichandran
Issue Date:June 2011
pp. 1801-1807
We consider the problem of fitting one or more subspaces to a collection of data points drawn from the subspaces and corrupted by noise/outliers. We pose this problem as a rank minimization problem, where the goal is to decompose the corrupted data matrix ...
 
Using global bag of features models in random fields for joint categorization and segmentation of objects
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By D. Singaraju,R. Vidal
Issue Date:June 2011
pp. 2313-2319
We propose to bridge the gap between Random Field (RF) formulations for joint categorization and segmentation (JCaS), which model local interactions among pixels and superpixels, and Bag of Features categorization algorithms, which use global descriptors. ...
 
Sparse subspace clustering
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By E. Elhamifar, R. Vidal
Issue Date:June 2009
pp. 2790-2797
We propose a method based on sparse representation (SR) to cluster data drawn from multiple low-dimensional linear or affine subspaces embedded in a high-dimensional space. Our method is based on the fact that each point in a union of subspaces has a SR wi...
 
Intrinsic mean shift for clustering on Stiefel and Grassmann manifolds
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By H.E. Cetingul, R. Vidal
Issue Date:June 2009
pp. 1896-1902
The mean shift algorithm, which is a nonparametric density estimator for detecting the modes of a distribution on a Euclidean space, was recently extended to operate on analytic manifolds. The extension is extrinsic in the sense that the inherent optimizat...
 
Histograms of oriented optical flow and Binet-Cauchy kernels on nonlinear dynamical systems for the recognition of human actions
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By R. Chaudhry, A. Ravichandran, G. Hager, R. Vidal
Issue Date:June 2009
pp. 1932-1939
System theoretic approaches to action recognition model the dynamics of a scene with linear dynamical systems (LDSs) and perform classification using metrics on the space of LDSs, e.g. Binet-Cauchy kernels. However, such approaches are only applicable to t...
 
Are Software Analytics Efforts Worthwhile for Small Companies? The Case of Amisoft
Found in: IEEE Software
By R. Robbes,R. Vidal,M. C. Bastarrica
Issue Date:September 2013
pp. 46-53
Amisoft, a Chilean software company with 43 employees, successfully uses software analytics in its projects. These support a variety of strategic and tactical decisions, resulting in less overwork of employees. However, the analytics done at Amisoft are ve...
 
View-invariant dynamic texture recognition using a bag of dynamical systems
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By A. Ravichandran, R. Chaudhry, R. Vidal
Issue Date:June 2009
pp. 1651-1657
In this paper, we consider the problem of categorizing videos of dynamic textures under varying view-point. We propose to model each video with a collection of linear dynamics systems (LDSs) describing the dynamics of spatiotemporal video patches. This bag...
 
P-brush: Continuous valued MRFs with normed pairwise distributions for image segmentation
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By D. Singaraju, L. Grady, R. Vidal
Issue Date:June 2009
pp. 1303-1310
Interactive image segmentation traditionally involves the use of algorithms such as graph cuts or random walker. Common concerns with using graph cuts are metrication artifacts (blockiness) and the shrinking bias (bias towards shorter boundaries). The rand...
 
A nonparametric Riemannian framework for processing high angular resolution diffusion images (HARDI)
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By A. Goh, C. Lenglet, P.M. Thompson, R. Vidal
Issue Date:June 2009
pp. 2496-2503
High angular resolution diffusion imaging has become an important magnetic resonance technique for in vivo imaging. Most current research in this field focuses on developing methods for computing the orientation distribution function (ODF), which is the pr...
 
Load Balancing in WLANs through IEEE 802.11k Mechanisms
Found in: Computers and Communications, IEEE Symposium on
By E.Garcia Villegas, R. Vidal Ferré, J. Paradells Aspas
Issue Date:June 2006
pp. 844-850
Current growth in the number of IEEE 802.11 wireless LAN networks, whether they be to provide cordless access to private home or enterprise networks, or to provide public access in Hot-Spots, brings the need to apply smart load balancing techniques with th...
 
Sparse Subspace Clustering: Algorithm, Theory, and Applications
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By E. Elhamifar,R. Vidal
Issue Date:November 2013
pp. 2765-2781
Many real-world problems deal with collections of high-dimensional data, such as images, videos, text, and web documents, DNA microarray data, and more. Often, such high-dimensional data lie close to low-dimensional structures corresponding to several clas...
 
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