Local binary patterns and its variants for face recognition

Meena, K.; Suruliandi, A.

doi:10.1109/icrtit.2011.5972286

Cited by 40 publications

(19 citation statements)

References 9 publications

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“…Then, in this section, we explain the various approaches to facial recognition such as: Facial recognition is a category of biometric software that maps an individual's facial features mathematically and stores the data as a face print. The software uses deep learning algorithms to compare a live capture or digital image to the stored faceprint in order to verify an individual's identity [8].…”

Section: B Face Recognitionmentioning

confidence: 99%

Face Detection and Recognition Techniques: A Survey

Bhosale¹,

Dhanashri²,

Namrata³

2018

International Journal of Advanced Research in Computer and Comm

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The biometric is a study of human behavior and features. Face recognition is a technique of biometric. Various approaches are used for it. Authentication & Identification has become major issue in today's digital world. Face recognition plays a significant role in authentication & identification. In this paper several existing face detection and recognition approaches are analyzed and discussed. Each approached is discussed briefly & compared with the other in terms of key evaluation parameters. As face detection is the elementary yet an important step towards automatic face recognition, main goal of this paper is to come up with an approach that is a good candidate for face detection and face recognition.

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Section: B Face Recognitionmentioning

confidence: 99%

Face Detection and Recognition Techniques: A Survey

Bhosale¹,

Dhanashri²,

Namrata³

2018

International Journal of Advanced Research in Computer and Comm

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“…Once it transform through LDSMT, [5,1,3,4,2,3,5,2] and for sign [1,1,1,1,-1,-1,-1 binary code the -1 is refer as 0 and become 8…”

Section: Clbp -Completed Local Binary Patternmentioning

confidence: 99%

“…Based on TABLE 1, the LBPV g recognition rate of 62% compared to conv CLBP and conventional LBP which is of val (13) as [5,1,3,4,-2,-3,the magnitude is 1,1] and convert to 8-bit 11110001. rity between the in the database, as…”

Section: A the Feature Extraction Technique Of Lbpmentioning

confidence: 99%

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Evaluation of LBP-based face recognition techniques

Faudzi

Yahya

2014

2014 5th International Conference on Intelligent and Advanced Systems (ICIAS)

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Face recognition is a popular technique in identifying human features. In certain application such as recognizing criminals from video surveillance, where no other physical trait is available, face recognition is the most practical and assessable human recognition method. For this reason, face recognition continue to attract large research interest among image processing community. In this paper, Local Binary Pattern (LBP) texture method is used to characterize the image features. Four derivatives of LBP are evaluated in order to select the best LBP technique for face recognition system. The derivatives are conventional LBP, Center Symmetric Local Binary Pattern (CS-LBP), Local Binary Pattern Variance (LBPV) and Completed Local Binary Pattern (CLBP). The evaluations of the LBPs are conducted using Japanese female facial expression (JAFFE) and author personal databases using recognition rate and run time value as the performance metrics. In particular, three different experiments are conducted, namely LBPs in an ideal environment, LBPs in different level of contrast and LBPs in the presence of additive Gaussian noise. The results indicates that based on average recognition rate, the LBPV gives the best performance among the LBPs and consider as the most reliable LBP derivative in change of illumination and noisy environments.

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“…In the last years, the LBP descriptor [15] has been successful in several applications, such as texture recognition [16], face detection/recognition [17], and facial expression recognition [18], due to its powerful characteristics. However, the fact that the LBP descriptor does not consider any global spatial information is a disadvantage in the case of hand gestures.…”

Section: Volumetric Spatiograms Of Local Binary Patterns (Vs-lbp)mentioning

confidence: 99%

Human–computer interaction based on visual hand-gesture recognition using volumetric spatiograms of local binary patterns

Maqueda

del-Blanco

Jaureguizar

et al. 2015

Computer Vision and Image Understanding

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A more natural, intuitive, user-friendly, and less intrusive Human-Computer interface for controlling an application by executing hand gestures is presented. For this purpose, a robust vision-based hand-gesture recognition system has been developed, and a new database has been created to test it. The system is divided into three stages: detection, tracking, and recognition. The detection stage searches in every frame of a video sequence potential hand poses using a binary Support Vector Machine classifier and Local Binary Patterns as feature vectors. These detections are employed as input of a tracker to generate a spatio-temporal trajectory of hand poses. Finally, the recognition stage segments a spatio-temporal volume of data using the obtained trajectories, and compute a video descriptor called Volumetric Spatiograms of Local Binary Patterns (VS-LBP), which is delivered to a bank of SVM classifiers to perform the gesture recognition. The VS-LBP is a novel video descriptor that constitutes one of the most important contributions of the paper, which is able to provide much richer spatio-temporal information than other existing approaches in the state of the art with a manageable computational cost. Excellent results have been obtained outperforming other approaches of the state of the art.

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Local binary patterns and its variants for face recognition

Cited by 40 publications

References 9 publications

Face Detection and Recognition Techniques: A Survey

Face Detection and Recognition Techniques: A Survey

Evaluation of LBP-based face recognition techniques

Human–computer interaction based on visual hand-gesture recognition using volumetric spatiograms of local binary patterns

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