2019 International Conference on Cyberworlds (CW)最新文献_第5页

How does Augmented Reality Improve the Play Experience in Current Augmented Reality Enhanced Smartphone Games? 增强现实如何改善当前增强现实智能手机游戏的游戏体验?

2019 International Conference on Cyberworlds (CW) Pub Date : 2019-10-01 DOI: 10.1109/CW.2019.00079

Matthias Wölfel, Melinda C. Braun, Sandra Beuck

引用次数: 3

Electroencephalography Based Motor Imagery Classification Using Unsupervised Feature Selection 基于脑电图的无监督特征选择运动图像分类

2019 International Conference on Cyberworlds (CW) Pub Date : 2019-10-01 DOI: 10.1109/CW.2019.00047

Abdullah Al Shiam, M. Islam, Toshihisa Tanaka, M. I. Molla

{"title":"Electroencephalography Based Motor Imagery Classification Using Unsupervised Feature Selection","authors":"Abdullah Al Shiam, M. Islam, Toshihisa Tanaka, M. I. Molla","doi":"10.1109/CW.2019.00047","DOIUrl":"https://doi.org/10.1109/CW.2019.00047","url":null,"abstract":"The major challenge in Brain Computer Interface (BCI) is to obtain reliable classification accuracy of motor imagery (MI) task. This paper mainly focuses on unsupervised feature selection for electroencephalography (EEG) classification leading to BCI implementation. The multichannel EEG signal is decomposed into a number of subband signals. The features are extracted from each subband by applying spatial filtering technique. The features are combined into a common feature space to represent the effective event MI classification. It may inevitably include some irrelevant features yielding the increase of dimension and mislead the classification system. The unsupervised discriminative feature selection (UDFS) is employed here to select the subset of extracted features. It effectively selects the dominant features to improve classification accuracy of motor imagery task acquired by EEG signals. The classification of MI tasks is performed by support vector machine. The performance of the proposed method is evaluated using publicly available dataset obtained from BCI Competition III (IVA). The experimental results show that the performance of this method is better than that of the recently developed algorithms.","PeriodicalId":117409,"journal":{"name":"2019 International Conference on Cyberworlds (CW)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134094401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

An Interactive System for Modeling Fish Shapes 鱼类形状建模的交互式系统

2019 International Conference on Cyberworlds (CW) Pub Date : 2019-10-01 DOI: 10.1109/CW.2019.00076

Masayuki Tamiya, Y. Dobashi

引用次数: 0

Person Identification from Visual Aesthetics Using Gene Expression Programming 基于基因表达编程的视觉美学人物识别

2019 International Conference on Cyberworlds (CW) Pub Date : 2019-10-01 DOI: 10.1109/CW.2019.00053

Brandon Sieu, M. Gavrilova

{"title":"Person Identification from Visual Aesthetics Using Gene Expression Programming","authors":"Brandon Sieu, M. Gavrilova","doi":"10.1109/CW.2019.00053","DOIUrl":"https://doi.org/10.1109/CW.2019.00053","url":null,"abstract":"The last decade has witnessed an increase in online human interactions, covering all aspects of personal and professional activities. Identification of people based on their behavior rather than physical traits is a growing industry, spanning diverse spheres such as online education, e-commerce and cyber security. One prominent behavior is the expression of opinions, commonly as a reaction to images posted online. Visual aesthetic is a soft, behavioral biometric that refers to a person's sense of fondness to a certain image. Identifying individuals using their visual aesthetics as discriminatory features is an emerging domain of research. This paper introduces a new method for aesthetic feature dimensionality reduction using gene expression programming. The advantage of this method is that the resulting system is capable of using a tree-based genetic approach for feature recombination. Reducing feature dimensionality improves classifier accuracy, reduces computation runtime, and minimizes required storage. The results obtained on a dataset of 200 Flickr users evaluating 40000 images demonstrates a 94% accuracy of identity recognition based solely on users' aesthetic preferences. This outperforms the best-known method by 13.5%.","PeriodicalId":117409,"journal":{"name":"2019 International Conference on Cyberworlds (CW)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126084260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Automatic Image Enhancement Taking into Account User Preference 考虑用户偏好的自动图像增强

2019 International Conference on Cyberworlds (CW) Pub Date : 2019-10-01 DOI: 10.1109/CW.2019.00070

Yuri Murata, Y. Dobashi

引用次数: 3

Stylized Line Drawing of 3D Models using CNN 使用CNN的3D模型的风格化线条绘制

2019 International Conference on Cyberworlds (CW) Pub Date : 2019-10-01 DOI: 10.1109/CW.2019.00015

Mitsuhiro Uchida, S. Saito

引用次数: 1

Human Movements Classification Using Multi-channel Surface EMG Signals and Deep Learning Technique 基于多通道表面肌电信号和深度学习技术的人体运动分类

2019 International Conference on Cyberworlds (CW) Pub Date : 2019-10-01 DOI: 10.1109/CW.2019.00051

Jianhua Zhang, C. Ling, Sunan Li

{"title":"Human Movements Classification Using Multi-channel Surface EMG Signals and Deep Learning Technique","authors":"Jianhua Zhang, C. Ling, Sunan Li","doi":"10.1109/CW.2019.00051","DOIUrl":"https://doi.org/10.1109/CW.2019.00051","url":null,"abstract":"Electromyography (EMG) signals can be used for human movements classification. Nonetheless, due to their nonlinear and time-varying properties, it is difficult to classify the EMG signals and it is critical to use appropriate algorithms for EMG feature extraction and pattern classification. In literature various machine learning (ML) methods have been applied to the EMG signal classification problem in question. In this paper, we extracted four time-domain features of the EMG signals and use a generative graphical model, Deep Belief Network (DBN), to classify the EMG signals. A DBN is a fast, greedy deep learning algorithm that can rapidly find a set of optimal weights of a deep network with many hidden layers. To evaluate the DBN model, we acquired EMG signals, extracted their time-domain features, and then utilized the DBN model to classify human movements. The real data analysis results are presented to show the effectiveness of the proposed deep learning technique for both binary and 4-class recognition of human movements using the measured 8-channel EMG signals. The proposed DBN model may find applications in design of EMG-based user interfaces.","PeriodicalId":117409,"journal":{"name":"2019 International Conference on Cyberworlds (CW)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125494127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Detection of Humanoid Robot Design Preferences Using EEG and Eye Tracker 基于脑电图和眼动仪的仿人机器人设计偏好检测

2019 International Conference on Cyberworlds (CW) Pub Date : 2019-10-01 DOI: 10.1109/CW.2019.00044

Yisi Liu, Fan Li, L. Tang, Zirui Lan, Jian Cui, O. Sourina, Chun-Hsien Chen

{"title":"Detection of Humanoid Robot Design Preferences Using EEG and Eye Tracker","authors":"Yisi Liu, Fan Li, L. Tang, Zirui Lan, Jian Cui, O. Sourina, Chun-Hsien Chen","doi":"10.1109/CW.2019.00044","DOIUrl":"https://doi.org/10.1109/CW.2019.00044","url":null,"abstract":"Currently, many modern humanoid robots have little appeal due to their simple designs and bland appearances. To provide recommendations for designers and improve the designs of humanoid robots, a study of human's perception on humanoid robot designs is conducted using Electroencephalogram (EEG), eye tracking information and questionnaires. We proposed and carried out an experiment with 20 subjects to collect the EEG and eye tracking data to study their reaction to different robot designs and the corresponding preference towards these designs. This study can possibly give us some insights on how people react to the aesthetic designs of different humanoid robot models and the important traits in a humanoid robot design, such as the perceived smartness and friendliness of the robots. Another point of interest is to investigate the most prominent feature of the robot, such as the head, facial features and the chest. The result shows that the head and facial features are the focus. It is also discovered that more attention is paid to the robots that appear to be more appealing. Lastly, it is affirmed that the first impressions of the robots generally do not change over time, which may imply that a good humanoid robot design impress the observers at first sight.","PeriodicalId":117409,"journal":{"name":"2019 International Conference on Cyberworlds (CW)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114890485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Music in the Air with Leap Motion Controller 音乐在空中与跳跃运动控制器

2019 International Conference on Cyberworlds (CW) Pub Date : 2019-10-01 DOI: 10.1109/cw.2019.00018

A. Sourin

引用次数: 1

Vehicle Rear-Lamp Detection at Nighttime via Probabilistic Bitwise Genetic Algorithm 基于概率位遗传算法的夜间车辆尾灯检测

2019 International Conference on Cyberworlds (CW) Pub Date : 2019-10-01 DOI: 10.1109/CW.2019.00027

Takumi Nakane, Tatsuya Takeshita, Shogo Tokai, Chao Zhang

引用次数: 2