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Power LBP: A novel texture operator for smiling and neutral facial display classification

Power LBP: A novel texture operator for smiling and neutral ...

引用

15th Annual International Conference on Computational Science (ICCS)

作者： Smolka, Bogdan Nurzynska, Karolina Silesian Tech Univ Inst Automat Control Ul Akad 16 PL-44100 Gliwice Poland Silesian Tech Univ Inst Informat PL-44100 Gliwice Poland

Texture operators are commonly used to describe image content for many purposes. Recently they found its application in the task of emotion recognition, especially using local binary patterns method, LBP. This paper introduces a novel texture operator called power LBP, which defines a new ordering schema based on absolute intensity differences. Its definition as well as interpretation are given. The performance of suggested solution is evaluated on the problem of smiling and neutral facial display recognition. In order to evaluate the power LBP operator accuracy, its discriminative capacity is compared to several members of the LBP family. Moreover, the influence of applied classification approach is also considered, by presenting results for k-nearest neighbour, support vector machine, and template matching classifiers. Furthermore, results for several databases are compared.

关键词： power LBP local binary patterns classification emotion recognition

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Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped binary patterns

Emotion Recognition in the Wild via Convolutional Neural Net...

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2015 ACM International Conference on Multimodal Interaction

作者： Levi, Gil Hassner, Tal Open Univ Israel Raanana Israel USC Informat Sci Inst Marina Del Rey CA USA

ISBN: (纸本)9781450339124

We present a novel method for classifying emotions from static facial images. Our approach leverages on the recent success of Convolutional Neural Networks (CNN) on face recognition problems. Unlike the settings often assumed there, far less labeled data is typically available for training emotion classification systems. Our method is therefore designed with the goal of simplifying the problem domain by removing confounding factors from the input images, with an emphasis on image illumination variations. This, in an effort to reduce the amount of data required to effectively train deep CNN models. To this end, we propose novel transformations of image intensities to 3D spaces, designed to be invariant to monotonic photometric transformations. These are applied to CASIA Webface images which are then used to train an ensemble of multiple architecture CNNs on multiple representations. Each model is then fine-tuned with limited emotion labeled training data to obtain final classification models. Our method was tested on the Emotion Recognition in the Wild Challenge (EmotiW 2015), Static Facial Expression Recognition sub-challenge (SFEW) and shown to provide a substantial, 15.36% improvement over baseline results (40% gain in performance).

关键词： Emotion Recognition Deep Learning local binary patterns EmotiW 2015 Challenge

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Automatic Polyp Detection: A Comparative Study 37

Automatic Polyp Detection: A Comparative Study

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37th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： El Khatib, Alaa Werghi, Naoufel Al-Ahmad, Hussain Khalifa Univ Elect & Comp Engn Dept Sharjah U Arab Emirates

ISBN: (纸本)9781424492701

In this work we present a performance comparison between a set of different state-of-the-art image descriptors for the automatic detection of polyps in colonoscopy videos. This set includes: local binary patterns, 2-dimensional Gabor filters, wavelet-based texture, and histogram of oriented gradients. We use these descriptors in conjunction with support vector machine or nearest neighbor classifiers to classify candidate regions, which in turn are selected using the maximally stable extremal regions algorithm. We present performance scores on the ASU-Mayo Clinic polyp database.

关键词： Gabor filters biological tissues cancer medical image processing pattern classification support vector machines video signal processing wavelet transforms 2D Gabor filters ASU-Mayo Clinic polyp database automatic polyp detection colonoscopy videos image descriptors local binary patterns nearest neighbor classifiers support vector machine wavelet-based texture Colonoscopy Databases Feature extraction Support vector machines Training Videos

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LBP and Irregular Graph Pyramids 16th

LBP and Irregular Graph Pyramids

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16th International Conference on Computer Analysis of Images and patterns (CAIP)

作者： Cerman, Martin Gonzalez-Diaz, Rocio Kropatsch, Walter Vienna Univ Technol PRIP Grp A-1040 Vienna Austria Univ Seville Sch Comp Engn Dept Appl Math Seville Spain

ISBN: (纸本)9783319231174;9783319231167

In this paper, a new codification of local binary patterns (LBP) is given using graph pyramids. The LBP code characterizes the topological category (local max, min, slope, saddle) of the gray level landscape around the center region. Given a 2D grayscale image I, our goal is to obtain a simplified image which can be seen as "minimal" representation in terms of topological characterization of I. For this, a method is developed based on merging regions and Minimum Contrast Algorithm.

关键词： local binary patterns Irregular graph pyramid Primal and dual graph Topological characterization Minimum contrast algorithm

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Spoofing Countermeasure Based on Analysis of Linear Prediction Error 16

Spoofing Countermeasure Based on Analysis of Linear Predicti...

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16th Annual Conference of the International-Speech-Communication-Association (INTERSPEECH 2015)

作者： Janicki, Artur Warsaw Univ Technol Inst Telecommun Warsaw Poland

ISBN: (纸本)9781510817906

In this paper a novel speaker verification spoofing countermeasure based on analysis of linear prediction error is presented. The method analyses the energy of the prediction error, prediction gain and temporal parameters related to the prediction error signal. The idea of the proposed algorithm and its implementation is described in detail. Various binary classifiers were researched to separate human and spoof classes. When tested on the corpora provided for the ASVspoof 2015 Challenge, the proposed countermeasure yielded much better results than the baseline spoofing detector based on local binary patterns (LBP). It is hoped that the proposed method can help in developing a generalised countermeasure able to detect spoofing attacks based on different variants of speech synthesis, voice conversion, and, potentially, also other spoofing algorithms.

关键词： speaker verification spoofing linear prediction local binary patterns binary classification

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Feature to Feature Matching for LBP Based Face Recognition 14th

Feature to Feature Matching for LBP Based Face Recognition

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14th Mexican International Conference on Artificial Intelligence (MICAI)

作者： Lenc, Ladislav Kral, Pavel Univ W Bohemia Fac Sci Appl Dept Comp Sci & Engn Plzen 30614 Czech Republic Univ W Bohemia Fac Sci Appl NTIS New Technol Informat Soc Plzen 30614 Czech Republic

ISBN: (纸本)9783319271019;9783319271002

This paper presents a novel face recognition method called local binary patterns with Feature to Feature Matching (LBP-FF). Contrary to other LBP approaches, we do not focus on the operator itself, however we would like to improve the matching procedure. The current LBP based approaches concatenate all feature vectors into one vector and then compare these large vectors. By contrast, our method compares the features separately. A sophisticated distance measure composed from two parts is used for face comparison. Chi square distance and histogram intersection metrics are utilized for vector distance computation. The proposed approach is evaluated on four face corpora: AT&T, FERET, AR and CTK database. We experimentally show that our method significantly outperforms all compared state-of-the-art methods on all the databases. It is also worth of noting that the. CTK corpus is a novel face dataset composed of the images taken in real-world conditions and is freely available for research purposes at http://*** or upon request to the authors.

关键词： Automatic face recognition Czech News Agency LBP with Feature to Feature Matching LBP-FF local binary patterns

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3D Face Recognition Using local Features Matching on Sphere Depth Representation 10th

3D Face Recognition Using Local Features Matching on Sphere ...

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10th Chinese Conference on Biometric Recognition (CCBR)

作者： Wang, Hanchao Mu, Zhichun Zeng, Hui Huang, Mingming Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China

ISBN: (纸本)9783319254173;9783319254166

This paper proposes a 3D face recognition approach using sphere depth image, which is robust to pose variations in unconstrained environments. The input 3D face point clouds is first transformed into sphere depth images, and then represented as a 3DLBP image to enhance the distinctiveness of smooth and similar facial depth images. An improved SIFT algorithm is applied in the following matching process. The improved SIFT algorithm employs the learning to rank approach to select the keypoints with higher stability and repeatability instead of manually rule-based method used by the original SIFT algorithm. The proposed face recognition method is evaluated on CASIA 3D face database. And the experimental results show our approach has superior performance than many existing methods for 3D face recognition and handles pose variations quite well.

关键词： 3D face recognition Sphere depth image local binary patterns Learning to rank

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SPEED-OPTIMIZED FREE-VIEWPOINT RENDERING BASED ON DEPTH LAYERING 9

SPEED-OPTIMIZED FREE-VIEWPOINT RENDERING BASED ON DEPTH LAYE...

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3DTV Conference The True Vision Capture Transmission and Display of 3D Video 3DTV CON

作者： Chuchvara, Aleksandra Suominen, Olli Georgiev, Mihail Gotchev, Atanas Tampere Univ Technol Tampere Finland

ISBN: (纸本)9781467380904

In this paper free-viewpoint rendering is addressed and a new fast approach for virtual views synthesis from view-plus-depth 3D representation is proposed. Depth layering in disparity domain is employed in order to optimally approximate the scene geometry by a set of constant depth layers. This approximation facilitates the use of connectivity information for segment-based forward warping of the reference layer map, producing a complete virtual view layer map containing no cracks or holes. The warped layer map is used to guide the disocclusions inpainting process of the synthesized texture map. For this purpose, a speed-optimized patch-based inpainting approach is proposed. In contrast to the existing methods, patch similarity function is based on local binary patterns descriptors. Such binary representation allows for efficient processing and comparison of patches, as well as compact storage and reuse of previously calculated binary descriptors. The experimental results demonstrate real-time capability of the proposed method even for CPU-based implementation, while the quality is comparable with other view synthesis approaches.

关键词： free-viewpoint rendering depth-image-based rendering view-plus-depth depth map layer-based disocclusion inpainting local binary patterns real time

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Dominant LBP Considering Pattern Type for Facial Image Representation 18th

Dominant LBP Considering Pattern Type for Facial Image Repre...

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18th International Conference on Image Analysis and Processing (ICIAP)

作者： Sagheer, Alaa Saad, Shimaa King Faisal Univ Coll Comp Sci & Informat Technol Dept Comp Sci Al Hufuf Saudi Arabia Aswan Univ Fac Sci Ctr Artificial Intelligence & Robot Aswan Egypt

ISBN: (纸本)9783319232348;9783319232331

Facial image representation plays an important role in computer vision and image processing applications. This paper introduces a novel feature selection method, dominant LBP considering pattern type (DLBP-CPT), capable to capture, effectively, the most reliable and robust dominant patterns in face images. In contrast to the Dominant LBP (DLBP) approach, we take into account the dominant pattern types information. We find that pattern type represents essential information that should be included, especially, in facial image representation across illumination. We apply the proposed method with the conventional LBP and the angular difference LBP (AD-LBP) operators. It is shown in this paper, that the proposed DLBP-CPT and DAD-LBP-CPT descriptors are more reliable to represent the dominant pattern information in the facial images than either the conventional uniform LBP or other dominant LBP approaches.

关键词： local binary patterns Facial representation Feature selection Face identification

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REAL-TIME DYNAMIC TEXTURE RECOGNITION USING RANDOM SAMPLING AND DIMENSION REDUCTION

REAL-TIME DYNAMIC TEXTURE RECOGNITION USING RANDOM SAMPLING ...

引用

IEEE International Conference on Image Processing (ICIP)

作者： Gunay, Osman Cetin, A. Enis Bilkent Univ Dept Elect & Elect Engn TR-06800 Ankara Turkey

ISBN: (纸本)9781479983391

In this paper, we propose a real-time dynamic texture recognition method using projections onto random hyperplanes and deep neural network filters. We divide dynamic texture videos into spatio-temporal blocks and extract features using local binary patterns (LBP). We reduce the computational cost of the exhaustive LBP method by using randomly sampled subset of pixels in a given spatio-temporal block. We use random hyperplanes and deep neural network filters to reduce the dimensionality of the final feature vectors. We test the performance of the proposed method in a dynamic texture database. We also propose an application of the proposed method to real-time detection of flames in infrared videos. We observe that the approach based on random hyperplanes produces the best results.

关键词： Dynamic texture local binary patterns real-time random hyperplanes deep neural networks

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