Sparse representation is being proved to be effective for many tasks in the field of pattern recognition. In this paper, an efficient classification algorithm based on concentrative sparse representation will be proposed to address the problem caused by insufficient training samples in each class. We ...
Sparse representation based classification codes the test sample as a sparse linear combination of training samples and classifies the test sample class by class using the class representation errorAnd plurality voting is widely utilized combination strategies in pattern recognitionIn this paper, a face ...
The use of sparse representation (SR) and collaborative representation (CR) for pattern classification has been widely studied in tasks such as face recognition and object categorization. Despite the success of SR/CR based classifiers, it is still arguable whether it is the \\ell_{1} \\ell_{...
Sparse representation based classification (SRC) has been proved to be a simple, effective and robust solution to face recognition. As it gets popular, doubts on the necessity of enforcing sparsity starts coming up, and primary experimental results showe
稀疏表示分类(Sparse Representation for Classification,简称SRC)是一项在模式识别和信号处理中应用广泛的技术。它基于这样一个概念:一个信号(比如图像、语音等)可以用一个较大的字典中的一些基向量稀疏地表示。 想象一下,有一个巨大的图书馆(字典),其中每一本书(字典中的基向量)代表了一个特定的模式或特征。如果...
In recent years, sparse representation-based classification (SRC) has made great progress in face recognition (FR). However, SRC emphasizes noise sparsity too much and it is not suitable for the real world. In this paper, we propose a robust l2,1-norm Sparse Representation framework that const...
Moreover, the proposed method seamlessly and elegantly integrates low-rank learning and sparse representation-based classification. Extensive experiments on three challenging face databases demonstrate the effectiveness and robustness of JLSRC in comparison with the state-of-the-art methods....
Sparse representation for machine learning has been exploited in past years. Several sparse representation based classification algorithms have been developed for some applications, for example, face recognition. In this paper, we propose an improved sparse representation based classification algorithm. Firstl...
第二篇:Sparse Representation Based Fisher Discrimination Dictionary Learning for Image Classification这篇文章是偶然情况下一个同学给我看的,看了之后就感觉灰常不错,对我们这种初出茅庐的菜鸟启发性很大。这篇文章其实是对上篇文章的一个改进,从题目我们就可以看出这篇文章把SRC和Fisher线性判别做了一个综合,文章...
We merge illumination normalization and component features into the framework of Sparse Representation-based Classification (SRC) for face recognition across illumination. Unlike most SRC-based face recognition which constructs a dictionary from a training set with sufficient illumination variation, the propos...