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检索条件"主题词=Local binary patterns"

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Laughter Detection based on the Fusion of local binary patterns, Spectral and Prosodic Features 18

Laughter Detection based on the Fusion of Local Binary Patte...

引用

18th IEEE International Workshop on Multimedia Signal Processing (MMSP)

作者： Bedoya, Stefany Falk, Tiago H. Univ Quebec INRS EMT Montreal PQ Canada

ISBN: (纸本)9781509037247

Today, great focus has been placed on context-aware human-machine interaction, where systems are aware not only of the surrounding environment, but also about the mental/affective state of the user. Such knowledge can allow for the interaction to become more human-like. To this end, automatic discrimination between laughter and speech has emerged as an interesting, yet challenging problem. Typically, audio- or video-based methods have been proposed in the literature;humans, however, are known to integrate both sensory modalities during conversation and/or interaction. As such, this paper explores the fusion of support vector machine classifiers trained on local binary pattern (LBP) video features, as well as speech spectral and prosodic features as a way of improving laughter detection performance. Experimental results on the publicly-available MAHNOB Laughter database show that the proposed audio-visual fusion scheme can achieve a laughter detection accuracy of 93.3%, thus outperforming systems trained on audio or visual features alone.

关键词： speech laughter spectral features cepstral features local binary patterns

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Description of Visual Content in Dermoscopy Images Using Joint Histogram of Multiresolution local binary patterns and local Contrast 16th

Description of Visual Content in Dermoscopy Images Using Joi...

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16th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL)

作者： Naeem, Sidra Riaz, Farhan Hassan, Ali Nisar, Rida Natl Univ Sci & Technol Dept Comp Engn Coll Elect & Mech Engn Islamabad Pakistan

ISBN: (纸本)9783319248349;9783319248332

Melanoma is a deadly form of skin lesion for which the mortality rate can be significantly reduced, if detected at an early stage. Clinical findings have shown that an early detection of melanoma can be done by an inspection of visual characteristics of some specific regions (lesions) of the skin. This paper proposes a pattern recognition system that includes three vital stages to conform the analysis of skin lesions by the clinicians: segmentation, feature extraction, and classification. Segmentation is performed using active contours with creasness features. The feature extraction phase consists of a variant of local binary pattern (LBP) in which joint histogram of LBP pattern along with the contrast of the patterns are used to extract scale adaptive patterns at each pixel. Classification was performed using support vector machines. Experimental results demonstrate the superiority of the proposed feature set over several other state-of-the-art texture feature extraction methods for melanomas detection. The results indicate the significance of contrast of the pattern along with LBP patterns.

关键词： Texture local binary patterns Dermoscopy

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Face Description with local binary patterns and local Ternary patterns: Improving Face Recognition Performance Using Similarity Feature-Based Selection and Classification Algorithm

Face Description with Local Binary Patterns and Local Ternar...

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International Symposium on Computer, Consumer and Control (IS3C)

作者： Tran, Chi-Kien Lee, Tsair-Fwu Chang, Liyun Chao, Pei-Ju Natl Kaohsiung Univ Appl Sci Dept Elect Engn Kaohsiung 80778 Taiwan I Shou Univ Dept Med Imaging & Radiol Sci Kaohsiung Taiwan Kaohsiung Chang Gung Mem Hosp Dept Radiat Oncol Kaohsiung Taiwan

ISBN: (纸本)9781479952779

In recent years, the binary coding of face image features, such as local binary patterns (LBP) and local ternary patterns (LTP) have become popular in face recognition systems. These local feature descriptors provide a simple and powerful means for texture description. In this paper, we present a novel approach, which uses these descriptors to represent face images, and a similarity feature-based selection and classification algorithm to improve recognition rate. The face image is first divided into small regions from which LBP and LTP histograms are extracted and concatenated into a single feature vector. The proposed algorithm is used to select the similarity features of training set and classify the face image. The experiments are conducted on the ORL Database of Faces and the Extended Yale Face Database B. The results clearly show the superiority of the proposed algorithm.

关键词： Face recognition similarity feature local binary patterns local ternary patterns local feature

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Face Recognition with Directional local binary patterns

Face Recognition with Directional Local Binary Patterns

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6th Chinese Conference on Biometric Recognition (CCBR)

作者： Shen, Linlin He, Jinwen Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen 518060 Guangdong Peoples R China

ISBN: (纸本)9783642254482

A novel local feature descriptor, namely Directional local binary patterns (DLBP), was proposed in this paper and applied for face recognition. The descriptor first extracts directional edge information, then codes these information using local binary patterns (LBP). When applied for face recognition, a face image is divided into a number of small sub-windows, DLBP histogram extracted from each sub-window are then concatenated to form a global description of the face. The proposed method was extensively evaluated on two publicly available databases. i.e. the FERET face database and the PolyU-NIRED near-infrared face database. Experimental results show advantages of DLBP over LBP and Directional binary Code (DBC).

关键词： Directional local binary patterns local binary patterns Directional binary Code Face Recognition

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Improved texture retrieval by combining different variants of local binary patterns 8

Improved texture retrieval by combining different variants o...

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International Conference on Electrical and Computer Engineering

作者： Mohammed, Nabeel Rana, Sohel Univ Asia Pacific Dept CSE Dhaka Bangladesh

ISBN: (纸本)9781479941667

This paper proposes the combination of different variants of local binary patterns for texture retrieval. Recent studies have shown that LBP features extracted at multiple resolutions give the best performance for a standard texture retrieval collection. Techniques have been proposed to create a multi-dimensional histogram of these features. In this study we use a simpler approach. We hypothesize that the different variants of LBP may actually extract slightly different but useful image information. If this were the case, then using them in combination will result in further improved performance, compared to using each one independently. We demonstrate this by using LBP, LBp(ri), and LBp(u2) features in combination. We take ideas from the GNU Image Finding Tool (GIFT), and use separate normalisation to ensure the different feature vector lengths do not bias the system towards one of the features. We performed experiments on the two standard texture collections. Our results demonstrate that combining the different LBP features do indeed result in improved performance. In fact, for one of the collections (Outex_TR_00000) collections, using our method give better performance than the current state-of-the-art.

关键词： Image retrieval local binary patterns Separate normalisation

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Prostate Segmentation with local binary patterns Guided Active Appearance Models

Prostate Segmentation with Local Binary Patterns Guided Acti...

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Conference on Medical Imaging 2011 - Image Processing

作者： Ghose, Soumya Oliver, Arnau Marti, Robert Llado, Xavier Freixenet, Jordi Vilanova, Joan C. Meriaudeau, Fabrice Univ Girona Comp Vis & Robot Grp Campus MontiliviEdifici P 4 Girona 17071 Catalonia Spain

ISBN: (纸本)9780819485045

Real-time fusion of Magnetic Resonance (MR) and Trans Rectal Ultra Sound (TRUS) images aid in the localization of malignant tissues in TRUS guided prostate biopsy. Registration performed on segmented contours of the prostate reduces computational complexity and improves the multimodal registration accuracy. However, accurate and computationally efficient segmentation of the prostate in TRUS images could be challenging in the presence of heterogeneous intensity distribution inside the prostate gland, and other imaging artifacts like speckle noise, shadow regions and low Signal to Noise Ratio (SNR). In this work, we propose to enhance the texture features of the prostate region using local binary patterns (LBP) for the propagation of a shape and appearance based statistical model to segment the prostate in a multi-resolution framework. A parametric model of the propagating contour is derived from Principal Component Analysis (PCA) of the prior shape and texture information of the prostate from the training data. The estimated parameters are then modified with the prior knowledge of the optimization space to achieve an optimal segmentation. The proposed method achieves a mean Dice Similarity Coefficient (DSC) value of 0.94 +/- 0.01 and a mean segmentation time of 0.68 +/- 0.02 seconds when validated with 70 TRUS images of 7 datasets in a leave-one-patient-out validation framework. Our method performs computationally efficient and accurate prostate segmentation in the presence of intensity heterogeneities and imaging artifacts.

关键词： Prostate Segmentation Active Appearance Model Texture local binary patterns

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Virus Texture Analysis Using local binary patterns and Radial Density Profiles

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16th Iberoamerican Congress on Pattern Recognition

作者： Kylberg, Gustaf Uppstrom, Mats Sintorn, Ida-Maria Ctr Image Anal Lagerhyddsvagen 2 SE-75105 Uppsala Sweden Vironova AB SE-11330 Stockholm Sweden

ISBN: (纸本)9783642250842

We investigate the discriminant power of two local and two global texture measures on virus images. The viruses are imaged using negative stain transmission electron microscopy. local binary patterns and a multi scale extension are compared to radial density profiles in the spatial domain and in the Fourier domain. To assess the discriminant potential of the texture measures a Random Forest classifier is used. Our analysis shows that the multi scale extension performs better than the standard local binary patterns and that radial density profiles in comparison is a rather poor virus texture discriminating measure. Furthermore, we show that the multi scale extension and the profiles in Fourier domain are both good texture measures and that they complement each other well, that is, they seem to detect different texture properties. Combining the two, hence, improves the discrimination between virus textures.

关键词： virus morphology texture analysis local binary patterns radial density profiles

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Objective Grading of Facial Paralysis Using local binary patterns in Video Processing

Objective Grading of Facial Paralysis Using Local Binary Pat...

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30th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society

作者： He, Shu Soraghan, John J. O'Reilly, Brian F. Univ Strathclyde Dept Elect & Elect Engn Glasgow G1 1XQ Lanark Scotland Southern Gen Hosp Inst Neurol Sci Glasgow Lanark Scotland

ISBN: (纸本)9781424418145

This paper presents a novel framework for objective measurement of facial paralysis in biomedial videos. The motion information in the horizontal and vertical directions and the appearance features on the apex frames are extracted based on the local binary patterns (LBP) on the temporal-spatial domain in each facial region. These features are temporally and spatially enhanced by the application of block schemes. A multi-resolution extension of uniform LBP is proposed to efficiently combine the micro-patterns and large-scale patterns into a feature vector, which increases the algorithmic robustness and reduces noise effects while still retaining computational simplicity. The symmetry of facial movements is measured by the Resistor-Average Distance (RAD) between LBP features extracted from the two sides of the face. Support Vector Machine (SVM) is applied to provide quantitative evaluation of facial paralysis based on the House-Brackmann (H-B) Scale. The proposed method is validated by experiments with 197 subject videos, which demonstrates its accuracy and efficiency.

关键词： Facial Paralysis Measurement local binary patterns Facial Image Analysis

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Extended Gaussian-filtered local binary patterns for colonoscopy image classification

Extended Gaussian-filtered Local Binary Patterns for colonos...

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IEEE International Conference on Computer Vision (ICCV)

作者： Manivannan, Siyamalan Wang, Ruixuan Trucco, Emanuele Univ Dundee Sch Comp CVIP Dundee DD1 4HN Scotland

ISBN: (纸本)9781479930227

local binary patterns (LBP) and its variants are widely used for texture classification. In this paper we propose a new variant of LBP descriptor called the extended Gaussian filtered local binary patterns (xGF-LBP) which is robust to illumination changes, noise and captures more informative edge-like features for classification. Experiments on a colonoscopy image dataset with 2100 images for binary ('normal' or 'abnormal') classification show that the proposed xGF-LBP descriptor significantly outperforms the standard LBP descriptor and its considered variants.

关键词： colonoscopy image classification local binary patterns binary pattern binary LBP gene LBP Image classification Colonoscopy variants illumination Lighting Descriptors Noise

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Extracting local binary patterns from Image Key Points: Application to Automatic Facial Expression Recognition

Extracting Local Binary Patterns from Image Key Points: Appl...

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18th Scandinavian Conference on Image Analysis (SCIA)

作者： Feng, Xiaoyi Lai, Yangming Mao, Xiaofei Peng, Jinye Jiang, Xiaoyue Hadid, Abdenour Northwestern Polytech Univ Coll Elect & Informat Xian 710072 Peoples R China Univ Oulu Ctr Machine Vis Res Dept Comp Sci & Engn SF-90100 Oulu Finland

ISBN: (纸本)9783642388866;9783642388859

Facial expression recognition has widely been investigated in the literature. The need of accurate facial alignment has however limited the deployment of facial expression systems in real-world applications. In this paper, a novel feature extraction method is proposed. It is based on extracting local binary patterns (LBP) from image key points. The face region is first segmented into six facial components (left eye, right eye, left eyebrow, right eyebrow, nose, and mouth). Then, local binary patterns are extracted only from the edge points of each facial component. Finally, the local binary pattern features are collected into a histogram and fed to an SVM classifier for facial expression recognition. Compared to the traditional LBP methodology extracting the features from all image pixels, our proposed approach extracts LBP features only from a set of points of face components, yielding in more compact and discriminative representations. Furthermore, our proposed approach does not require face alignment. Extensive experimental analysis on the commonly used JAFFE facial expression benchmark database showed very promising results, outperforming those of the traditional local binary pattern approach.

关键词： local binary patterns Facial expression Recognition Key Points

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