Journal ArticleDOI
Visual object tracking via sample-based Adaptive Sparse Representation (AdaSR)
TLDR
A new approach for visual object tracking based on Sample-Based Adaptive Sparse Representation (AdaSR), which ensures that the tracked object is adaptively and compactly expressed with predefined samples, which is better than those of several representative tracking methods.About:
This article is published in Pattern Recognition.The article was published on 2011-09-01. It has received 81 citations till now. The article focuses on the topics: Video tracking & Sparse approximation.read more
Citations
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Journal ArticleDOI
Robust Visual Tracking Using Structurally Random Projection and Weighted Least Squares
TL;DR: This paper proposes a real-time visual tracking method based on structurally random projection (RP) and weighted least squares (WLS) techniques, and introduces background templates to the linear representation framework to enhance the discriminative capability of the tracker.
Journal ArticleDOI
Robust visual tracking with structured sparse representation appearance model
Tianxiang Bai,Youfu Li +1 more
TL;DR: A structured sparse representation appearance model for tracking an object in a video system that preferably matches the practical visual tracking problem by taking the contiguous spatial distribution of occlusion into account and is integrated with a stochastic affine motion model to form a particle filter framework for visual tracking.
Journal ArticleDOI
Discriminative Object Tracking via Sparse Representation and Online Dictionary Learning
TL;DR: With the help of sparse representation and online updated discriminative dictionary, the KP part are more robust than the traditional method to reject the incorrect matches and eliminate the outliers.
Journal ArticleDOI
Visual abnormal behavior detection based on trajectory sparse reconstruction analysis
TL;DR: A novel abnormal behavior detection approach by introducing trajectory sparse reconstruction analysis (SRA), solved by L1-norm minimization, leading to that a few of dictionary samples are used when reconstructing a behavior trajectory, which guarantees that the proposed approach is valid even when the dictionary set is very small.
Journal ArticleDOI
Robust Visual Tracking via Basis Matching
TL;DR: This paper proposes a novel tracking by matching framework for robust tracking based on basis matching rather than point matching, which outperforms those of several state-of-the-art methods.
References
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Journal ArticleDOI
Regression Shrinkage and Selection via the Lasso
TL;DR: A new method for estimation in linear models called the lasso, which minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant, is proposed.
Proceedings ArticleDOI
Histograms of oriented gradients for human detection
Navneet Dalal,Bill Triggs +1 more
TL;DR: It is shown experimentally that grids of histograms of oriented gradient (HOG) descriptors significantly outperform existing feature sets for human detection, and the influence of each stage of the computation on performance is studied.
Journal ArticleDOI
Atomic Decomposition by Basis Pursuit
TL;DR: Basis Pursuit (BP) is a principle for decomposing a signal into an "optimal" superposition of dictionary elements, where optimal means having the smallest l1 norm of coefficients among all such decompositions.
Journal ArticleDOI
Robust Face Recognition via Sparse Representation
TL;DR: This work considers the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise, and proposes a general classification algorithm for (image-based) object recognition based on a sparse representation computed by C1-minimization.
Proceedings ArticleDOI
Good features to track
Jianbo Shi,Tomasi +1 more
TL;DR: A feature selection criterion that is optimal by construction because it is based on how the tracker works, and a feature monitoring method that can detect occlusions, disocclusions, and features that do not correspond to points in the world are proposed.