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Spatial patch blending for artefact reduction in pattern-based inpainting techniques

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15th international conference on Computer Analysis of Images and patterns, CAIP 2013

作者： Daisy, Maxime Tschumperlé, David Lézoray, Olivier Image Team 6 Bd Marechal Juin 14050 Caen France

ISBN: (纸本)9783642402456

Patch-based (or "pattern-based") inpainting, is a popular processing technique aiming at reconstructing missing regions in images, by iteratively duplicating blocks of known image data (patches) inside the area to fill in. this kind of method is particularly effective to process wide image areas, thanks to its ability to reconstruct textured data. Nevertheless, "pathological" geometric configurations often happen, leading to visible reconstruction artefacts on inpainted images, whatever the chosen pattern-based inpainting algorithm. In this paper we focus on these problematic cases and propose a generic spatial-blending technique that can be adapted to any type of patch-based inpainting methods in order to reduce theses problematic artefacts. © 2013 Springer-Verlag.

关键词： Iterative methods

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Incremental Locality Preserving Nonnegative Matrix Factorization

Incremental Locality Preserving Nonnegative Matrix Factoriza...

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6th international conference on Advanced Computational Intelligence (ICACI)

作者： Zheng, Jianwei Chen, Yu Jin, Yiting Wang, Wanliang Zhejiang Univ Technol Coll Comp Sci Hangzhou 310023 Zhejiang Peoples R China

ISBN: (纸本)9781467363433

Recently nonnegative matrix factorization (NMF) has become a popular dimension reduction method and it has been successfully applied to image processing and pattern recognition. In this paper, we propose an incremental locality preserving nonnegative matrix factorization (ILPNMF) method, which is aimed to discover the manifold structure embedded in high-dimensional space that deals well with large scale data. By assuming that the newly added samples do not change the encoding vectors of old samples, we present a cost function for online learning. then we use projected gradient method to solve the update rule of the cost function. Experimental results show that ILPNMF provides a better parts-based representation compared with INMF and it is faster than the batch one LPNMF.

关键词： matrix decomposition Cost functions Nonnegative gradient methods e-learning REDUCTION MEthODS Incremental pattern recognition Image processing

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Automatic Facial Expression recognition for Image Sequences

Automatic Facial Expression Recognition for Image Sequences

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6th international conference on Contemporary Computing (IC3)

作者： Sarawagi, Varsha Arya, K. V. Banasthali Vidyapith AIM & ACT Deptt Jaipur Rajasthan India ABV Indian Inst Informat Technol & Management Dept Comp Sci & Engn Gwalior India

ISBN: (纸本)9781479901920

A human face has a distinct and unique characteristics which make it play a very critical role in recognizing facial expression in a "facial expression recognition system." Identifying or as we say it detection of expressions plays a big and significant role in a facial expression recognition system. If we talk about a human being it becomes an easy task recognize expression in any particular image sequence, but at the same time if we talk about fully automated systems not many are currently available or capable to do so. the field of facial expression recognition do have many different applications and its importance, it might be used to have an interaction between a human being and a computer, here a user, without using his hands, can give commands or instruct to the computer system with the help of facial expression recognition system. Quite a few options are available to identify a face in an image in an efficient and accurate manner, although similar cannot be said for features detection in a video sequence frame. Most systems are still dependent on manual operations for same. Here in this paper we have emphasizes on color normalization and facial feature extraction which uses LBP (Local Binary pattern) as an effective feature detection approach, where the existing algorithms have been modified to improve the facial expression recognition accuracy. the recognition accuracy on the Indian database is observe to be 94.7\%.

关键词： Local Binary pattern Active State Method Support Vector Machine Vertical Time Backward Feature Selection

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Emerging Intelligent Computing Technology and Applications: 9th international conference, ICIC 2013, Nanning, China, July 28-31, 2013. Proceedings 1

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丛书名： Communications in Computer and Information Science 375

2013年

作者： Zhifeng Hao, Jinlong Huang, Ruichu Cai, Wen Wen (auth.), De-Shuang Huang, Phalguni Gupta, Ling Wang, Michael Gromiha (eds.)

ISBN: (数字)9783642396786

ISBN: (纸本)9783642396779;9783642396786

this book constitutes the refereed proceedings of the 9th international conference on Intelligent Computing, ICIC 2013, held in Nanning, China, in July 2013. the 192 revised full papers presented in the three volumes LNCS 7995, LNAI 7996, and CCIS 375 were carefully reviewed and selected from 561 submissions. the papers in this volume (CCIS 375) are organized in topical sections on Neural Networks; Systems Biology and Computational Biology; Computational Genomics and Proteomics; Knowledge Discovery and Data Mining; Evolutionary Learning and Genetic Algorithms; Machine Learning theory and Methods; Biomedical Informatics theory and Methods; Particle Swarm Optimization and Niche Technology; Unsupervised and Reinforcement Learning; Intelligent Computing in bioinformatics; Intelligent Computing in Finance/Banking; Intelligent Computing in Petri Nets/Transportation Systems; Intelligent Computing in Signal Processing; Intelligent Computing in pattern recognition; Intelligent Computing in Image Processing; Intelligent Computing in Robotics; Intelligent Computing in Computer Vision; Special Session on Biometrics System and Security for Intelligent Computing; Special Session on Bio-inspired Computing and Applications; Computer Human Interaction using Multiple Visual Cues and Intelligent Computing; Special Session on Protein and Gene bioinformatics: Analysis, Algorithms and Applications.

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Facial Expression recognition with Regional Features Using Local Binary patterns

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15th international conference on Computer Analysis of Images and patterns (CAIP)

作者： Majumder, Anima Behera, Laxmidhar Subramanian, Venkatesh K. Indian Inst Technol Kanpur Dept Elect Engn Kanpur Uttar Pradesh India

ISBN: (纸本)9783642402616

this paper presents a simple yet efficient and completely automatic approach to recognize six fundamental facial expressions using Local Binary patterns (LBPs) texture features. A system is proposed that can automatically locate four important facial regions from which the uniform LBPs features are extracted and concatenated to form a 236 dimensional enhanced feature vector to be used for six fundamental expressions recognition. the features are trained using three widely used classifiers: Naive bayes, Radial Basis Function Network (RBFN) and three layered Multi-layer Perceptron (MLP3). the notable feature of the proposed method is the use of few preferred regions of the face to extract the LBPs features as opposed to the use of entire face. the experimental results obtained from MMI database show proficiency of the proposed features extraction method.

关键词： Facial expression recognition local binary pattern facial features extraction radial basis function network multilayer perceptron naive bayes

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Traffic Congestion Classification using Motion Vector Statistical Features

Traffic Congestion Classification using Motion Vector Statis...

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6th international conference on Machine Vision (ICMV)

作者： Riaz, Amina Khan, Shoab A. NUST Dept Comp Engn Coll E&ME Rawalpindi Pakistan

ISBN: (纸本)9780819499967

Due to the rapid increase in population, one of the major problems faced by the urban areas is traffic congestion. In this paper we propose a method for classifying highway traffic congestion using motion vector statistical properties. Motion vectors are estimated using pyramidal Kanada-Lucas-Tomasi (KLT) tracker algorithm. then motion vector features are extracted and are used to classify the traffic patterns into three categories: light, medium and heavy. Classification using neural network, on publicly available dataset, shows an accuracy of 95.28%, with robustness to environmental conditions such as variable luminance. Our system provides a more accurate solution to the problem as compared to the systems previously proposed.

关键词： pattern recognition Motion recognition Video Processing Neural Network Application

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Gait-based gender classification using persistent homology 1

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18th Iberoamerican Congress on pattern recognition, CIARP 2013

作者： Leon, Javier Lamar Cerri, Andrea Reyes, Edel Garcia Diaz, Rocio Gonzalez Patterns Recognition Department Advanced Technologies Application Center 7a # 21812 e/ 218 y 222 Rpto. Siboney Playa C.P. 12200 La Habana Cuba IMATI - CNR via de Marini 6 16149 Genova Italy Applied Math Dept. School of Computer Engineering University of Seville Seville Spain

ISBN: (数字)9783642418273

ISBN: (纸本)9783642418266

In this paper, a topological approach for gait-based gender recognition is presented. First, a stack of human silhouettes, extracted by background subtraction and thresholding, were glued through their gravity centers, forming a 3D digital image I. Second, different filters (i.e. particular orders of the simplices) are applied on ∂K (I) (a simplicial complex obtained from I) which capture relations among the parts of the human body when walking. Finally, a topological signature is extracted from the persistence diagram according to each filter. the measure cosine is used to give a similarity value between topological signatures. the novelty of the paper is a notion of robustness of the provided method (which is also valid for gait recognition). three experiments are performed using all human-camera view angles provided in CASIA-B database1. the first one evaluates the named topological signature obtaining 98.3% (lateral view) of correct classification rates, for gender identification. the second one shows results for different human-camera distances according to training and test (i.e. training with a human-camera distance and test with a different one). the third one shows that upper body is more discriminative than lower body. © Springer-Verlag 2013.

关键词： Topology

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Adaptive Common Spatial pattern for Single-Trial EEG Classification in Multisubject BCI

Adaptive Common Spatial Pattern for Single-Trial EEG Classif...

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6th international IEEE EMBS conference on Neural Engineering (NER)

作者： Song, Xiaomu Yoon, Suk-Chung Perera, Viraga Widener Univ Dept Elect Engn One Univ Pl Chester PA 19013 USA

ISBN: (纸本)9781467319690

Common Spatial patterns (CSP) is a widely used spatial filtering method for electroencephalogram (EEG)-based brain computer interface (BCI). It is a supervised technique that needs subject specific training data. Due to the non-stationary nature of EEG, EEG signal may exhibit significant inter-and intra-subject variation. Consequently, spatial filters learned from one subject may not perform well for EEG data acquired from another subject performing a same task, or even from the same subject at a different time. Various methods have been developed to improve CSP's multisubject performance by adding regularizing terms into the learning process. Most of these methods include target subjects' training data in the CSP learning, and the trained spatial filters are fixed when applied to classification. In this work, an adaptive CSP method was proposed to classify single trial EEG data from multiple subjects. the method does not require training data from target subjects, and updates spatial filters based on target subjects' data during the classification. three different methods were proposed to adapt the CSP learning to target subjects. Experimental results on motor imagery data indicate that the proposed method can efficiently integrate target subjects' information into the CSP learning, and provide better discrimination performance (about 20% increase in overall classification accuracy) than the standard CSP method for multisubject BCI.

关键词： brain-computer interfaces electroencephalography learning systems medical signal processing pattern recognition signal classification spatial filters

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theory and Practice of Model Transformations - 6th international conference, ICMT 2013, Proceedings

Theory and Practice of Model Transformations - 6th Internati...

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6th international conference on theory and Practice of Model Transformations, ICMT 2013

ISBN: (纸本)9783642388828

the proceedings contain 18 papers. the topics discussed include: streaming model transformations: scenarios, challenges and initial solutions;genetic-programming approach to learn model transformation rules from examples;walk your tree any way you want;on an automated translation of satellite procedures using triple graph grammars;the graph grammar library - a generic framework for chemical graph rewrite systems;a methodological approach for the coupled evolution of metamodels and ATL transformations;metamodel-specific coupled evolution based on dynamically typed graph transformations;robust real-time synchronization between textual and graphical editors;achieving practical genericity in model weaving through extensibility;a rete network construction algorithm for incremental pattern matching;and interactive visual analytics for efficient maintenance of model transformations.

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6th international conference on Informatics in Schools: Situation, Evolution, and Perspectives, ISSEP 2013

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6th international conference on Informatics in Schools: Situation, Evolution, and Perspectives, ISSEP 2013

ISBN: (纸本)9783642366161

the proceedings contain 17 papers. the special focus in this conference is on From Computer Usage to Computational thinking, Algorithmic, Computational thinking, Games and Retention of Competencies. the topics include: A first step towards a research framework for computer science education in schools;computer science in secondary schools in the UK;informatics in the French secondary curricula;informatics for all high school students;novice difficulties with interleaved pattern composition;blind pupils begin to solve algorithmic problems;location-based games in informatics education;using computer games as programming assignments for university students and secondary school pupils;the contribution of computer science to learning computational physics;constructionism and IBL in practice and motivation for studying stem;competence measurement and informatics standards in secondary education;on competence-based learning and neuroscience;categorization of pictures in tasks of the bebras contest and on using a Delphi process in informatics teacher education.

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