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International Conference on Fuzzy Systems and Knowledge Discovery

作者： Han Su Jiayun Zou Wenjie Wang Key Lab of Virtual Reality and Visual Computing of Sichuan Sichuan Normal University Chengdu China 610066|c|

ISBN: (纸本)9781467352512

In this paper, we present a novel method for activity analysis in outdoor environment. Difficulties, such as low resolution, shadows, long distances, and segmentation problems, usually exist in outdoor environment. To deal with these difficulties, the activity width sequence image which maintains 3D features using 2D representation is exploited to represent the silhouette structure information of each frame and dynamic properties of activity. The activity width vectors are converted to the gray value successively according to the order in activity sequence and the gray image is formed in spatio-temporal space. We regard the activity width sequence image as the texture and choose local binary patterns which is a powerful texture extraction operator to analyze the spatio-temporal pattern. The method is simple and effective. We test our method based on the outdoor database and the results are encouraging.

关键词： Human Activity Recognition local binary patterns Silhouette Width

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Multiplicative local binary patterns (MuLBP)

Multiplicative Local Binary Patterns (MuLBP)

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International Conference on Pattern Recognition Systems

作者： Marco Mora Marcelo Silva-Ibarra Monica Acevedo-Letelier Department of Computer Science Universidad Católica del Maule Chile Laboratory of Technological Research in Pattern Recognition Universidad Católica del Maule Chile Laboratory of Technological Research in Pattern Recognition Universidad Católica del Maule Chile

ISBN: (数字)9781839531088

Speckle is a multiplicative noise that greatly deteriorates images. In this paper a model of local binary patterns (LBP) adapted to images with speckle (MuLBP) is proposed. The multiplicative model is constructed by substituting the additive comparisons of the traditional LBP for multiplicative comparisons from the Bigeometric Calculus. The experiments were carried out considering the 10.824 images of the KTH-TIPS2, FMD, CASIA and UFI databases. To compare the additive and multiplicative models, the Euclidean distance between the LBP histograms of the image with noise and without noise is adopted. The results indicate that, the distance between the histograms, the image with noise with respect to the image without noise, is smaller for the multiplicative models than for the traditional additive models. The above means that, the multiplicative LBP represent in a better way the textures in images contaminated with speckle.

关键词： local binary patterns Speckle Bi-geometric calculus

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local gabor binary patterns based on Kullback-Leibler divergence for partially occluded face recognition

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IEEE SIGNAL PROCESSING LETTERS 2007年第11期14卷 875-878页

作者： Zhang, Wenchao Shan, Shiguang Chen, Xilin Gao, Wen Harbin Inst Technol Sch Comp Sci & Technol Harbin 150001 Peoples R China Chinese Acad Sci Comp Technol Inst ICT ISVISION FRJDL Beijing 150001 Peoples R China

The partial occlusion is one of the key issues in the face recognition community. To resolve the problem of partial occlusion, based on our previous work of local Gabor binary patterns (LGBP) for face recognition, we further propose Kullback-Leibler divergence (KLD)-based LGBP for partial occluded face recognition. The local property of LGBP face recognition is thoroughly used in the method, by introducing KLD between the LGBP feature of the local region and that of the non-occluded local region to estimate the probability of occlusion. The probability is used as the weight of the local region for the final feature matching. The experimental results on the AR face database demonstrate the effectiveness of the KLD-based LGBP face recognition method for partially occluded face images.

关键词： face recognition Gabor wavelets Kullback-Leibler divergence local binary patterns

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FACE RECOGNITION WITH STATISTICAL local binary patterns

FACE RECOGNITION WITH STATISTICAL LOCAL BINARY PATTERNS

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2009 International Conference on Machine Learning and Cybernetics(2009机器学习与控制论国际会议)

作者： LEI CHEN YUN-HONG WANG YI-DING WANG DI HUANG School of Computer Science and Engineering Beihang University Beijing 100191 China College of Information Engineering North China University of Technology Beijing 100041 China MI Department Ecole Centrale de Lyon France

In this work, we present a novel algorithm for face recognition named statistical local binary patterns (sLBP) . This is a further development of original local binary Pattern algorithm. Our method is applied for face recognition under visual light environment dealing with dramatically illumination varying on faces. After a statistical analysis on the distribution probability of the gray-level difference values between neighbor pixels, a mapping function is proposed to encode a wide range of these values into three binary bits. Three extension LBP layers are then generated Finally the uniform pattern histograms of all these layers in every divided region are concatenated as an enhanced local feature vector of the face image. Experimental results on FERET face database show considerable effectiveness and robustness of our proposed method.

关键词： Face recognition local binary patterns uniform pattern statistical analysis

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A Comparative Study of Geometry,Gabor Wavelets Representation and local binary patterns for Facial Expression Recognition

A Comparative Study of Geometry,Gabor Wavelets Representatio...

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2010 4th International Conference on Intelligent Information Technology Application (IITA2010)

作者： Qiang Zhou,Shiqing Zhang School of Physics and Electronic Engineering Taizhou University Taizhou,China

Facial expression recognition is an interesting and challenging problem and impacts important applications in many areas such as intelligent environments and multimodal human computer ***,Gabor wavelets representation and local binary patterns (LBP) are three types of successful facial features for facial expression *** this paper,the recognition performance of geometry,Gabor wavelets representation and LBP,was compared on facial expression recognition *** results on the popular JAFFE facial expression database demonstrate Gabor wavelets representation obtains the best performance,outperforming geometry and LBP.

关键词： facial expression recognition Geometry Garbor wavelets representation local binary patterns

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FAST FACIAL EXPRESSION RECOGNITION BASED ON local binary patterns

FAST FACIAL EXPRESSION RECOGNITION BASED ON LOCAL BINARY PAT...

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IEEE Canadian Conference on Electrical and Computer Engineering

作者： Rohit Verma Mohamed-Yahia Dabbagh Dept. of Electrical and Computer Engineering University of Waterloo

ISBN: (纸本)9781479900312

Automatic facial expression analysis is an interesting and challenging problem which impacts important applications in many areas such as human-computer interaction and data-driven animation. Deriving effective facial representative features from face images is a vital step towards successful expression recognition. In this paper, we evaluate facial representation based on statistical local features called local binary patterns (LBP) for facial expression recognition. Simulation results illustrate that LBP features are effective and efficient for facial expression recognition. A real-time implementation of the proposed approach is also demonstrated which can recognize expressions accurately at the rate of 4.8 frames per second.

关键词： Facial expression recognition local binary patterns Support vector machine AdaBoost Support Vector Network EXPRESSION ANALYSIS Facial Recognition expression recognition binary binary pattern ADABOOST Face LBP gene LBP computer human interaction

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AUTOMATIC CLASSIFICATION OF SKIN LESIONS USING GEOMETRICAL MEASUREMENTS OF ADAPTIVE NEIGHBORHOODS AND local binary patterns

AUTOMATIC CLASSIFICATION OF SKIN LESIONS USING GEOMETRICAL M...

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IEEE International Conference on Image Processing

作者： V. Gonzalez-Castro J. Debayle Y. Wazaefi M. Rahim C. Gaudy J. J. Grob B. Fertil Ecole Nat. Sup. des Mines de Saint-Etienne Lab. des Sciences de l'Information et des Systems Service de Dermatologie Hopital de la Timone

ISBN: (纸本)9781479983407

This paper introduces a method for characterizing and classifying skin lesions in dermoscopic color images with the goal of detecting which ones are melanoma (cancerous lesions). The images are described by means of the local binary patterns (LBPs) computed on geometrical feature maps of each color component of the image. These maps are extracted from geometrical measurements of the General Adaptive Neighborhoods (GAN) of the pixels. The GAN of a pixel is a region surrounding it and fitting its local image spatial structure. The performance of the proposed texture descriptor has been evaluated by means of an Artificial Neural Network, and it has been compared with the classical LBPs. Experimental results using ROC curves show that the GAN-based method outperforms the classical one and the dermatologists' predictions.

关键词： Melanoma Texture description General adaptive neighborhoods local binary patterns Melanoma Skin lesions binary pattern binary texture descriptor skin pixel Automatic classification color image AUTOMATIC ROC Curve images Artificial neural networks

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DOMINANT MULTI-DIMENSIONAL local binary patterns

DOMINANT MULTI-DIMENSIONAL LOCAL BINARY PATTERNS

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IEEE International Conference on Signal Processing, Communications and Computing

作者： Niraj P. Doshi Gerald Schaefer Department of Computer Science Loughborough University U.K.

ISBN: (纸本)9781479910267

local binary patterns (LBP) are known as a simple yet powerful texture descriptor encoding local neighbourhood properties. LBP descriptors can be calculated at different radii, leading to a multi-resolution texture characterisation. Multidimensional LBP (MD-LBP) utilises this concept, while also maintaining the relationships between the different scales by building a multi-dimensional histogram of LBP features. Although this has been shown to give good discriminatory power, the resulting feature vectors are also rather large. In this paper, we show that Dominant MD-LBP (D-MD-LBP), which utilises only dominant texture bins, provides an effective texture descriptor of reduced dimensionality as our experimental results, run on three benchmark datasets of the Outex test suite, confirm.

关键词： texture texture classification local binary patterns multi-dimensional LBP

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Image Retrieval Based on Contourlet Transform and local binary patterns

Image Retrieval Based on Contourlet Transform and Local Bina...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Qidong Zhang Jiantma Wu Liqun Gao School of Information Science & Engineering Northeastern University Shenyang 110004 china

ISBN: (纸本)9781424427994

A novel medical image retrieval algorithm based on texture is proposed. The contourlet transform combines non-separable and directional niters banks, and has multiscale and directional properties. The marginal distribution of contourlet transform coefficients is modeled by generalized Gaussian density. It is used for texture feature extraction in transform domain. Uniform local binary patterns have good rotation invariance. It extracts texture feature in spatial domain and his retrieval time is short. A texture feature extracting algorithm combined statistical features of the contourlet with block-based uniform local binary patterns is proposed further. The two texture feature were extracted in spatial domain and in transform domain, which are complementary. A database of medical images was retrieved by this algorithm. The result shows it can achieve a high precision of retrieval.

关键词： Texture feature Contourlet transform local binary patterns

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FACIAL EXPRESSION RECOGNITION USING CURVELET BASED local binary patterns

FACIAL EXPRESSION RECOGNITION USING CURVELET BASED LOCAL BIN...

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Ashirbani Saha Q.M. Jonathan Wu Department of Electrical and Computer Engineering University of Windsor Windsor ON Canada

ISBN: (纸本)9781424442959

This paper proposes the use of the combination of digital curvelet transform and local binary patterns for recognizing facial expressions from still images. The curvelet transform is applied to the image of a face at a specific scale and orientation. local binary patterns are extracted from the selected curvelet sub-bands to form the descriptive feature set of the expressions. The average of the features of a particular class of expression is considered as the representative feature set of that class. The expression recognition is performed using a nearest neighbor classifier with Chi-square as the dissimilarity metric. Experiments show that our method yields recognition rates of 93percent and 90percent in JAFFE and Cohn-Kanade databases respectively.

关键词： Facial Expression Recognition Curvelets local binary patterns binary binary pattern Facial Recognition expression recognition Nearest neighbor Facial Expression Wavelet Analysis Transform Still images

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