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检索条件"任意字段=8th International Conference on Computing and Pattern Recognition, ICCPR 2019"

共 395 条记录，以下是191-200 订阅

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Emotional State recognition with Micro-expressions and Pulse Rate Variability 20th

Emotional State Recognition with Micro-expressions and Pulse...

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20th international conference on Image Analysis and Processing (ICIAP)

作者： Belaiche, Reda Sabour, Rita Meziati Migniot, Cyrille Benezeth, Yannick Ginhac, Dominique Nakamura, Keisuke Gomez, Randy Yang, Fan Univ Bourgogne Franche Comte ImViA EA 7535 Dijon France Honda Res Inst Japan Co Ltd 8-1 Honcho Wako Saitama Japan

ISBN: (纸本)9783030306427;9783030306410

Machine learning has known a tremendous growth within the last years, and lately, thanks to that, some computer vision algorithms started to access what is difficult or even impossible to perceive by the human eye. It is then natural that scientists began looking for ways to probe humans' emotions and their psyche with this technology. In this paper, we study the feasibility of recognizing and classifying the abstract concept of emotional states from videos of people facing a regular RGB camera. We do so by using the barely perceptible micro facial expressions humans cannot control, as well as the spontaneous variations of the pulse rate that we estimated using remote photoplethysmography. We compare these two modalities and our experimental results show that it is possible to classify emotional states from these implicit information gathered from regular cameras with encouraging performances.

关键词： Affective computing Facial expressions LBP Pulse rate variability Remote photoplethysmography

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Optimization of Row pattern Matching over Sequence Data in Spark SQL 30th

Optimization of Row Pattern Matching over Sequence Data in S...

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30th international conference on Database and Expert Systems Applications (DEXA)

作者： Nakabasami, Kosuke Kitagawa, Hiroyuki Nasu, Yuya Railway Tech Res Inst Hikari Cho 2-8-38 Kokubunji Tokyo Japan Univ Tsukuba Ctr Computat Sci Tennodai 1-1-1 Tsukuba Ibaraki Japan Univ Tsukuba Grad Sch Syst & Informat Engn Tennodai 1-1-1 Tsukuba Ibaraki Japan

ISBN: (纸本)9783030276157;9783030276140

Due to the advance of information and communications technology and sensor technology, a large quantity of sequence data (time series data, log data, etc.) are generated and processed every day. Row pattern matching for the sequence data stored in relational databases was standardized as SQL/RPR in 2016. Today, in addition to relational databases, there are many frameworks for processing a large amount of data in parallel and distributed computing environments. they include MapReduce and Spark. Hive and Spark SQL enable us to code data analysis processes in SQL-like query languages. Row pattern matching is also beneficial in Hive and Spark SQL. However, computational cost of the row pattern matching process is large and it is needed to make this process efficient. In this paper, we propose two optimization methods to realize the reduction of computational cost for row pattern matching process. We focus on Spark and show design and implementation of the proposed methods for Spark SQL. We verify by the experiments that our optimization methods really contribute to the reduction of the processing time of Spark SQL queries including row pattern matching.

关键词： Sequence data pattern matching Row pattern recognition MATCH RECOGNIZE Spark SQL Optimization

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Human Posture recognition using Artificial Neural Networks 8

Human Posture Recognition using Artificial Neural Networks

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IEEE 8th international Advance computing conference (IACC)

作者： Kale, Hrishikesh Mandke, Prathamesh Mahajan, Hrishikesh Deshpande, Vedant COEP Dept Elect & Telecommun Engn Pune Maharashtra India

ISBN: (纸本)9781538666784

this paper proposes the use of artificial neural networks(ANNs) to classify human postures, using an invasive(intrusive) approach, into 6 categories namely standing, sitting, sleeping and bending - forward and backward. Human posture recognition has numerous applications in the field of healthcare analysis like patient monitoring, lifestyle analysis, elderly care etc. Most importantly, our solution is capable of classifying the aforementioned postures in real-time, by wirelessly(Wi-Fi) acquiring and processing the sensor data on a Raspberry-Pi device with minimal lag. A data-set of 44,800 samples was collected - from 3 subjects - which was used to train and test the neural *** experimenting and testing with a plethora of network architectures, an optimal neural network architecture(6-9-6) with suitable hyper-parameters was determined which gave an overall accuracy of 97.589%.

关键词： pattern-recognition neural-networks posture-recognition wearable-sensors accelerometers embedded systems real time movement classification sensor positioning

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Solving Machine Part Cell Formation Problem Using Genetic Algorithm Based Evolutionary computing 8th

Solving Machine Part Cell Formation Problem Using Genetic Al...

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8th international conference on Soft computing and pattern recognition (SoCPaR) / 8th international conference on Computational Aspects of Social Networks (CASoN)

作者： Sowmiya, N. Valarmathi, B. Gupta, N. Srinivasa VIT Univ Sch Informat Technol & Engn Vellore Tamil Nadu India VIT Univ Sch Informat Technol & Engn Dept Software & Syst Engn Vellore Tamil Nadu India VIT Univ Sch Mech Engn Vellore Tamil Nadu India

ISBN: (纸本)9783319606187;9783319606170

Machine part cell formation is the group technology problem, in which the parts with near similar machining requirements are grouped into part families and the corresponding machines into machine cells. In this paper, a genetic algorithm with a fine tuning procedure is proposed to solve the group technology problem considering only one process plan for each part. the grouping efficacy achieved by the proposed method is comparable to the existing methods in general and better for 11.42% of the datasets.

关键词： Genetic algorithm Clustering Cell formation Cellular manufacturing Grouping efficacy

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Applicability of Soft computing and Optimization Algorithms in Software Testing and Metrics - A Brief Review 8th

Applicability of Soft Computing and Optimization Algorithms ...

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8th international conference on Soft computing and pattern recognition (SoCPaR) / 8th international conference on Computational Aspects of Social Networks (CASoN)

作者： Sharma, Deepak Chandra, Pravin Guru Gobind Singh Indraprastha Univ Univ Sch Informat & Commun Technol Delhi 110078 India

ISBN: (纸本)9783319606187;9783319606170

In spite of many years of work by scientists and specialists on various software qualities, testing stays one of the most broadly honed and concentrated on methodologies for evaluating and improving software quality. Our objective, in this paper, is to present how optimization techniques provide solutions to different and difficult issues in different areas of software engineering. Optimization algorithms are mathematical procedures, which intends to best optimal results for the defect, fault, failure to accomplish tractability, strength, and low arrangement cost. In this paper, a comprehensive overview of software testing and metrics based on soft computing and optimization techniques is presented. In this survey, we try to explain some major problems like defect prediction, software fault prediction and their solutions by soft computing and optimization algorithms. the paper presents an overview of the usage of Mathematical optimization Algorithms and soft computing approaches.

关键词： Optimization algorithms Soft computing Software testing Metrics Software fault prediction

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Person Identification from Full-Body Movement Using String Grammar Fuzzy-Possibilistic C-Medians 8

Person Identification from Full-Body Movement Using String G...

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8th IEEE international conference on Control System, computing and Engineering (ICCSCE)

作者： Chantapakul, Watchanan Auephanwiriyakul, Sansanee theera-Umpon, Nipon Khunlertgit, Navadon Chiang Mai Univ Fac Engn Dept Comp Engn Chiang Mai Thailand Chiang Mai Univ Fac Engn Dept Elect Engn Chiang Mai Thailand Chiang Mai Univ Inst Biomed Engn Chiang Mai Thailand

ISBN: (纸本)9781538663240

Biometrics is a method to identify a person. However, there are several biometric techniques including face recognition, palm recognition, iris recognition, fingerprint recognition, and so on. there is a new approach in biometrics, i.e., identification using full-body movement. In this paper, we introduce a full-body movement in human identification using three Kinects. In particular, we utilize the string grammar fuzzy-possibilistic C-medians (sgFPCNIed) to group string sequences from skeleton frames into pose string, then group the pose string sequences of each person into multi-group to create multi prototypes for each person. the K-nearest neighbor is used to identify the person in the test process on 27 subjects. the system yields 73.33% correct classification on the best validation set of four-fold cross validation.

关键词： person identification syntactic pattern recognition string grammar fuzzy-possibilistic C-medians Kinect

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Social touch: stimuli-imitation protocol and automated recognition

Social touch: stimuli-imitation protocol and automated recog...

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international conference on Affective computing and Intelligent Interaction Workshops and Demos (ACIIW)

作者： Wail Elbani Institut des systè mes intelligents et de robotique Sorbonne Université CNRS UMR 7222 Paris France

Touch plays an important role in socio-emotional communication: a loving hug from a spouse, a comforting tap on the back by friend, a push from a stranger convey efficiently an emotion or an intent, specially when combined with other modalities such as audition and vision. In a parent-child relationship, the frequency of maternal touch is positively correlated to the a child early social development. In addition, Touch occurs frequently in patient care situation: a massage therapy, for instance, reduces chronic pain and alleviates anxiety when properly applied by a nurse. Underexplored by the human-machine-interaction and the affective computing literature, the purpose of this thesis is to integrate the sense of touch into interactive systems. In this paper we introduce a novel data collection framework for social touch and present the social touch recognition pipeline.

关键词： Videos Data collection Feature extraction Affective computing Tactile sensors

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Inference of an Extended Short Fiber Bundle Atlas Using Sulcus-Based Constraints for a Diffeomorphic Inter-subject Alignment

Inference of an Extended Short Fiber Bundle Atlas Using Sulc...

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21st international conference on Medical Image computing and Computer-Assisted Intervention (MICCAI) / 8th Eurographics Workshop on Visual computing for Biology and Medicine (VCBM) / international Workshop on Computational Diffusion MRI (CDMRI)

作者： Avila, Nicole Labra Lebenberg, Jessica Riviere, Denis Auzias, Guillaume Fischer, Clara Poupon, Fabrice Guevara, Pamela Poupon, Cyril Mangin, Jean-Francois CEA DRF Neurospin UNATI Gif Sur Yvette France Univ Paris Sud Paris Saclay France Univ Paris Diderot Sorbonne Paris Cite UMR S 1161 INSERM Paris France Aix Marseille Univ Inst Neurosci la Timone Marseille France Univ Concepcion Concepcion Chile CEA DRF Neurospin UNIRS Gif Sur Yvette France

ISBN: (纸本)9783030058319;9783030058302

We present a new framework for the creation of an extended atlas of short fiber bundles between 20 and 80 mm length. this method uses a Diffeomorphic inter-subject alignment procedure including information of cortical foldings and forces the accurate match of the sulci that have to be circumvented by the U-bundles. then, a clustering is performed to extract the most reproducible bundles across subjects. First results show an increased number of U-bundles consistently mapped in the general population compared with previous atlases created from the same database. Future analysis over this new extended Brain atlas may improve our understanding of the relationship between the folding pattern and the U-bundle variability. the ultimate aim will be the possibility to detect abnormal configurations induced by developmental issues.

关键词： White matter U-fiber U-bundles Short fiber bundles dMRI Diffusion MRI Brain atlas Bundle atlas Diffeomorphic alignment Sulcus base alignment Cortical folding pattern Sulci

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Contribution of temporal and multi-level body cues to emotion classification

Contribution of temporal and multi-level body cues to emotio...

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international conference on Affective computing and Intelligent Interaction and Workshops, ACII

作者： Nesrine Fourati Catherine Pelachaud Patrice Darmon UMANIS Research & Innovation Paris France CNRS ISIR Sorbonne University Paris France

the representation of expressive body movement is a critical step to automatically classify bodily expression of emotions. Using motion capture data, we study the contribution of different types of body features to the classification of emotions. In particular, we focus on the role played by temporal profiles of motion cues with regards to a set of multi-level body cues, including postural and dynamic ones.

关键词： Dynamics Machine learning three-dimensional displays Emotion recognition Magnetic heads End effectors Affective computing

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Multimodal and Temporal Perception of Audio-visual Cues for Emotion recognition

Multimodal and Temporal Perception of Audio-visual Cues for ...

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international conference on Affective computing and Intelligent Interaction and Workshops, ACII

作者： Esam Ghaleb Mirela Popa Stylianos Asteriadis University Maastricht Maastricht Netherlands

In Audio-Video Emotion recognition (AVER), the idea is to have a human-level understanding of emotions from video clips. there is a need to bring these two modalities into a unified framework, to effectively learn multimodal fusion for AVER. In addition, literature studies lack in-depth analysis and utilization of how emotions vary as a function of time. Psychological and neurological studies show that negative and positive emotions are not recognized at the same speed. In this paper, we propose a novel multimodal temporal deep network framework that embeds video clips using their audio-visual content, onto a metric space, where their gap is reduced and their complementary and supplementary information is explored. We address two research questions, (1) how audio-visual cues contribute to emotion recognition and (2) how temporal information impacts the recognition rate and speed of emotions. the proposed method is evaluated on two datasets, CREMA-D and RAVDESS. the study findings are promising, achieving the state-of-the-art performance on both datasets, and showing a significant impact of multimodal and temporal emotion perception.

关键词： Measurement Emotion recognition Visualization Task analysis Machine learning Affective computing Logic gates

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