Add to ORKGRecently, a new discriminative sparse representation method for robust face recognition that uses ℓ2-norm regularization was reported. In this paper, direct data-driven calculation of the balance parameter used in the objective function is presented. The modified system preserves the advantages of the original method while improving the recognition accuracy and making the system more automated, i.e., less dependent on the user\u27s input. Extensive simulations are performed on six face databases, namely, ORL, YALE, FERET, FEI, Cropped AR, and Georgia Tech. Sample results are given demonstrating the properties of the modified system
Face recognition became most important aspect in daily life. It has many application including biome...
In this paper, we consider the problem of robust face recognition using color information. In this c...
Abstract—A method, named competitive sparse representation classification (CSRC), is proposed for fa...
Abstract—When the feature dimension is larger than the number of samples the small sample-size probl...
Face recognition aims at endowing computers with the ability to identify different human beings acco...
In this paper we present a novel approach to face recog-nition. We propose an adaptation and extensi...
A sparse representation-based classifier (SRC) is developed and shows great potential for real-world...
Abstract—Face recognition is a popular topic in computer vision applications. Compressive sensing is...
Abstract: In this particular paper, we recommend a brand new sparse rendering primarily based group ...
Due to its potential applications, face recognition has been receiving more and more research attent...
Abstract With the increasing use of surveillance cameras, face recognition is being studied by many ...
In this chapter, we present a comprehensive framework for tackling the classical prob-lem of face re...
In this paper, we propose a coarse-to-fine face recognition method. This method consists of two stag...
This work proposes a novel framework of robust face recognition based on the sparse representation. ...
In this paper, we propose two innovative and computationally efficient algorithms for robust face re...
Face recognition became most important aspect in daily life. It has many application including biome...
In this paper, we consider the problem of robust face recognition using color information. In this c...
Abstract—A method, named competitive sparse representation classification (CSRC), is proposed for fa...
Abstract—When the feature dimension is larger than the number of samples the small sample-size probl...
Face recognition aims at endowing computers with the ability to identify different human beings acco...
In this paper we present a novel approach to face recog-nition. We propose an adaptation and extensi...
A sparse representation-based classifier (SRC) is developed and shows great potential for real-world...
Abstract—Face recognition is a popular topic in computer vision applications. Compressive sensing is...
Abstract: In this particular paper, we recommend a brand new sparse rendering primarily based group ...
Due to its potential applications, face recognition has been receiving more and more research attent...
Abstract With the increasing use of surveillance cameras, face recognition is being studied by many ...
In this chapter, we present a comprehensive framework for tackling the classical prob-lem of face re...
In this paper, we propose a coarse-to-fine face recognition method. This method consists of two stag...
This work proposes a novel framework of robust face recognition based on the sparse representation. ...
In this paper, we propose two innovative and computationally efficient algorithms for robust face re...
Face recognition became most important aspect in daily life. It has many application including biome...
In this paper, we consider the problem of robust face recognition using color information. In this c...
Abstract—A method, named competitive sparse representation classification (CSRC), is proposed for fa...