Face identification using linear regression

Naseem, Adnan; Togneri, Roberto; Bennamoun, Mohammed

doi:10.1109/icip.2009.5414539

Cited by 8 publications

(3 citation statements)

References 14 publications

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“…To the best of our knowledge, there have been no attempts in the literature of applying the LRC technique to the context of online character/pattern recognition till date. Most of the applications for which this technique has been adopted each only in face recognition [12], [13] The remaining parts of the paper is organized as follows. In section 2, we provide an algorithm for LRC approach.…”

Section: Introductionmentioning

confidence: 99%

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Linear regression for pattern recognition

Stephen

Jaganathan

2014

2014 International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE)

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This paper presents a novel method for pattern recognition problem in terms of linear regression. Normally, patterns from a single-object class lie on a linear subspace. Using this concept, we develop a linear model representing a probe image as a linear combination of class-specific galleries. Linear Regression Classification (LRC) algorithm for pattern recognition belongs to the category of nearest subspace classification. This algorithm is extensively evaluated on several standard digit and English character databases and our own Tamil character database. A comparative study with different databases and methods clearly reflects the efficiency of LRC approach for pattern recognition.

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Section: Introductionmentioning

confidence: 99%

“…In this paper, we use fairly simple but efficient linear regression based classification [10], [11], [12], [13] for the problem of pattern identification such as handwritten uppercase letters, digits, flowers and Tamil characters recognition. Samples from a specific object class are known to lie on a linear subspace.…”

Section: Introductionmentioning

confidence: 99%

Linear regression for pattern recognition

Stephen

Jaganathan

2014

2014 International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE)

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“…Using the idea that samples from a specific object class lie on a linear subspace [8] , a Linear Regression Classifier (LRC) was presented [9,10] . LRC can reduce the computation cost, however, its performance under conditions of varying expression and illumination is still improved.…”

Section: Introductionmentioning

confidence: 99%

Decision fusion for block linear regression classification based on confidence index

2011

The First Asian Conference on Pattern Recognition

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We consider the problem of recognizing human faces with varying expression and illumination, and a novel confidence index based block linear regression classification method is proposed. Our approach divides images into blocks, and each block is identified using the linear regression classifier separately. We develop a confidence index model to measure the recognition confidence of each block, and the final decision is achieved by aggregating individual results with the designed Bayesian decision fusion algorithm. The performances of our approach and conventional algorithms are evaluated under conditions of varying expression and illumination using benchmark databases, improvements demonstrate the proposed approach is robustness to both expression and illumination variations.

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An Incremental SRC Method for Face Recognition

Yang

2015

Lecture Notes in Computer Science

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Face identification using linear regression

Cited by 8 publications

References 14 publications

Linear regression for pattern recognition

Linear regression for pattern recognition

Decision fusion for block linear regression classification based on confidence index

An Incremental SRC Method for Face Recognition

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