Decomposition into low-rank plus additive matrices for background/foreground separation: A review for a comparative evaluation with a large-scale dataset
Background/foreground separation is the first step in video surveillance system to detect
moving objects. Recent research on problem formulations based on decomposition into low …
moving objects. Recent research on problem formulations based on decomposition into low …
Sparse representation for computer vision and pattern recognition
Techniques from sparse signal representation are beginning to see significant impact in
computer vision, often on nontraditional applications where the goal is not just to obtain a …
computer vision, often on nontraditional applications where the goal is not just to obtain a …
Video processing from electro-optical sensors for object detection and tracking in a maritime environment: A survey
We present a survey on maritime object detection and tracking approaches, which are
essential for the development of a navigational system for autonomous ships. The electro …
essential for the development of a navigational system for autonomous ships. The electro …
ViBe: A universal background subtraction algorithm for video sequences
O Barnich… - IEEE Transactions on …, 2010 - ieeexplore.ieee.org
This paper presents a technique for motion detection that incorporates several innovative
mechanisms. For example, our proposed technique stores, for each pixel, a set of values …
mechanisms. For example, our proposed technique stores, for each pixel, a set of values …
Robust principal component analysis?
This article is about a curious phenomenon. Suppose we have a data matrix, which is the
superposition of a low-rank component and a sparse component. Can we recover each …
superposition of a low-rank component and a sparse component. Can we recover each …
Compressive sensing: From theory to applications, a survey
S Qaisar, RM Bilal, W Iqbal… - Journal of …, 2013 - ieeexplore.ieee.org
Compressive sensing (CS) is a novel sampling paradigm that samples signals in a much
more efficient way than the established Nyquist sampling theorem. CS has recently gained a …
more efficient way than the established Nyquist sampling theorem. CS has recently gained a …
Robust visual tracking and vehicle classification via sparse representation
X Mei, H Ling - IEEE transactions on pattern analysis and …, 2011 - ieeexplore.ieee.org
In this paper, we propose a robust visual tracking method by casting tracking as a sparse
approximation problem in a particle filter framework. In this framework, occlusion, noise, and …
approximation problem in a particle filter framework. In this framework, occlusion, noise, and …
Robust visual tracking using ℓ1 minimization
X Mei, H Ling - 2009 IEEE 12th international conference on …, 2009 - ieeexplore.ieee.org
In this paper we propose a robust visual tracking method by casting tracking as a sparse
approximation problem in a particle filter framework. In this framework, occlusion, corruption …
approximation problem in a particle filter framework. In this framework, occlusion, corruption …