A fuzzy sliding mode controller is designed for controlling is proposed for speed tracking control of a separately excited DC motors (SEDCMs) in this paper. The method is based on Lyapounov stability, fuzzy and variable structure control theorems. First, the methodology of the fuzzy is used to estimate the unknown nonlinearities. When the system is in the sliding mode, the adaptive gain in the designed of the sliding surface is used to tackle the mismatched and unknown load torque disturbance. The result shows that the speed tracking error can be achieved in stability asymptotically.
{"title":"Design of the Fuzzy Sliding Mode Controller for DC Motor","authors":"Chih-Chin Wen, Chien-Wen Chung, Hui-Min Wang, Yaote Chang","doi":"10.1109/RVSP.2013.52","DOIUrl":"https://doi.org/10.1109/RVSP.2013.52","url":null,"abstract":"A fuzzy sliding mode controller is designed for controlling is proposed for speed tracking control of a separately excited DC motors (SEDCMs) in this paper. The method is based on Lyapounov stability, fuzzy and variable structure control theorems. First, the methodology of the fuzzy is used to estimate the unknown nonlinearities. When the system is in the sliding mode, the adaptive gain in the designed of the sliding surface is used to tackle the mismatched and unknown load torque disturbance. The result shows that the speed tracking error can be achieved in stability asymptotically.","PeriodicalId":6585,"journal":{"name":"2013 Second International Conference on Robot, Vision and Signal Processing","volume":"835 1","pages":"196-199"},"PeriodicalIF":0.0,"publicationDate":"2013-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83845101","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}
Yu-Hao Lee, Vincent Shieh, Chih-Lung Lin, Yung‐Jong Shiah
This study designed a system for evaluating personal stress by assessing activities of autonomic nervous system (ANS) using heart rate variability (HRV) analysis through Photoplethysmography (PPG) signal. To investigate the performance of stress relaxation, this study also designed an environment with personal preferences. The environment included visional, audio and olfactory elements. Five healthy college students were invited to five days stress task study. The personal preferences of environment were set before experimental procedure. The subjects were required to fill the State-Trait Anxiety Inventory (STAI), and PPG signal was acquired by the developed system during experimental procedure. The experimental procedure was composed with a sequence of initial rest for baseline, relaxation environment after rest, stress task and relaxation environment after stress task. Results indicated that a decrease in STAI and LF/HF was obtained during relaxation environment, whereas increase in STAI and LF/HF was obtained during stress task. These results suggested that an environment with personal preferences may improve helpfully for stress relaxation.
{"title":"A Stress Evaluation and Personal Relaxation System Based on Measurement of Photoplethysmography","authors":"Yu-Hao Lee, Vincent Shieh, Chih-Lung Lin, Yung‐Jong Shiah","doi":"10.1109/RVSP.2013.49","DOIUrl":"https://doi.org/10.1109/RVSP.2013.49","url":null,"abstract":"This study designed a system for evaluating personal stress by assessing activities of autonomic nervous system (ANS) using heart rate variability (HRV) analysis through Photoplethysmography (PPG) signal. To investigate the performance of stress relaxation, this study also designed an environment with personal preferences. The environment included visional, audio and olfactory elements. Five healthy college students were invited to five days stress task study. The personal preferences of environment were set before experimental procedure. The subjects were required to fill the State-Trait Anxiety Inventory (STAI), and PPG signal was acquired by the developed system during experimental procedure. The experimental procedure was composed with a sequence of initial rest for baseline, relaxation environment after rest, stress task and relaxation environment after stress task. Results indicated that a decrease in STAI and LF/HF was obtained during relaxation environment, whereas increase in STAI and LF/HF was obtained during stress task. These results suggested that an environment with personal preferences may improve helpfully for stress relaxation.","PeriodicalId":6585,"journal":{"name":"2013 Second International Conference on Robot, Vision and Signal Processing","volume":"12 1","pages":"182-185"},"PeriodicalIF":0.0,"publicationDate":"2013-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90827922","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}
Zizhu Fan, Ming Ni, Meibo Sheng, Zejiu Wu, Baogen Xu
In machine learning and pattern recognition, principal component analysis (PCA) is a very popular feature extraction and dimensionality reduction method for improving recognition performance or computational effiency. It has been widely used in numerous applications, especially in face recognition. Researches often use PCA integrating the nearest neighbor classifier (NNC) based on Euclidean distance (ED) to classify face images. We refer to this method as PCA+ED. However, we have observed that PCA can not significantly improve the recognition performance of NNC based on Euclidean distance through many experiments. The main reason is that PCA can not significantly change the Euclidean distance between samples when many components are used in classification. In order to improve the classification performance in face recognition, we use another distance measure, i.e., Mahalanobis distance (MD), in NNC after performing PCA in this paper. This approach is referred to as PCA+MD. Several experiments show that PCA+MD can significantly improve the classification performance in face recognition.
{"title":"Principal Component Analysis Integrating Mahalanobis Distance for Face Recognition","authors":"Zizhu Fan, Ming Ni, Meibo Sheng, Zejiu Wu, Baogen Xu","doi":"10.1109/RVSP.2013.27","DOIUrl":"https://doi.org/10.1109/RVSP.2013.27","url":null,"abstract":"In machine learning and pattern recognition, principal component analysis (PCA) is a very popular feature extraction and dimensionality reduction method for improving recognition performance or computational effiency. It has been widely used in numerous applications, especially in face recognition. Researches often use PCA integrating the nearest neighbor classifier (NNC) based on Euclidean distance (ED) to classify face images. We refer to this method as PCA+ED. However, we have observed that PCA can not significantly improve the recognition performance of NNC based on Euclidean distance through many experiments. The main reason is that PCA can not significantly change the Euclidean distance between samples when many components are used in classification. In order to improve the classification performance in face recognition, we use another distance measure, i.e., Mahalanobis distance (MD), in NNC after performing PCA in this paper. This approach is referred to as PCA+MD. Several experiments show that PCA+MD can significantly improve the classification performance in face recognition.","PeriodicalId":6585,"journal":{"name":"2013 Second International Conference on Robot, Vision and Signal Processing","volume":"7 1","pages":"89-92"},"PeriodicalIF":0.0,"publicationDate":"2013-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89013145","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}
Content-based image retrieval has become an important research area and consequently well performing retrieval algorithms are highly sought after. Texture features are often crucial for retrieval applications to achieve high precision, while local binary pattern (LBP) based texture descriptors have been shown to work well in this context. LBP features decsribe the texture neighbourhood of a pixel using simple comparison operators, and are often calculated based on varying neighbourhood radii to provide multi-resolution texture description. Furthermore, local contrast information can be integrated into LBP leading to LBP variance (LBPV) features. In conventional LBP methods, the histograms corresponding to different radii are simply concatenated resulting in a loss of information between different resolutions and added ambiguity. In this paper, we show that multi-dimensional LBP and LBPV histograms, which preserve the relationships between scales, provide improved texture retrieval performance. To cope with the exponential increase in terms of feature length, we show that application of principal component based feature reduction leads to very compact texture descriptors with high retrieval accuracy.
{"title":"Compact Multi-dimensional LBP Features for Improved Texture Retrieval","authors":"N. Doshi, G. Schaefer","doi":"10.1109/RVSP.2013.20","DOIUrl":"https://doi.org/10.1109/RVSP.2013.20","url":null,"abstract":"Content-based image retrieval has become an important research area and consequently well performing retrieval algorithms are highly sought after. Texture features are often crucial for retrieval applications to achieve high precision, while local binary pattern (LBP) based texture descriptors have been shown to work well in this context. LBP features decsribe the texture neighbourhood of a pixel using simple comparison operators, and are often calculated based on varying neighbourhood radii to provide multi-resolution texture description. Furthermore, local contrast information can be integrated into LBP leading to LBP variance (LBPV) features. In conventional LBP methods, the histograms corresponding to different radii are simply concatenated resulting in a loss of information between different resolutions and added ambiguity. In this paper, we show that multi-dimensional LBP and LBPV histograms, which preserve the relationships between scales, provide improved texture retrieval performance. To cope with the exponential increase in terms of feature length, we show that application of principal component based feature reduction leads to very compact texture descriptors with high retrieval accuracy.","PeriodicalId":6585,"journal":{"name":"2013 Second International Conference on Robot, Vision and Signal Processing","volume":"24 1","pages":"51-55"},"PeriodicalIF":0.0,"publicationDate":"2013-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77871581","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}
In this paper we present a short-term robot edutainment for junior high school students. The theme of this robotic course is the walking motion of multi-legged robot. We provided the students with the robot educational material that contains assembled leg parts. The students devised the configuration and motion of the robot using given constraints. We conducted a robot contest for the students to present their results in this robot course. As a result, by using limited materials, the students were able to produce a robot that shows their ingenuity. We could observe from a questionnaire about the course that the students were interested in science and robots.
{"title":"Robot Edutainment on Walking Motion of Multi-legged Robot","authors":"Noriko Takase, János Botzheim, N. Kubota","doi":"10.1109/RVSP.2013.59","DOIUrl":"https://doi.org/10.1109/RVSP.2013.59","url":null,"abstract":"In this paper we present a short-term robot edutainment for junior high school students. The theme of this robotic course is the walking motion of multi-legged robot. We provided the students with the robot educational material that contains assembled leg parts. The students devised the configuration and motion of the robot using given constraints. We conducted a robot contest for the students to present their results in this robot course. As a result, by using limited materials, the students were able to produce a robot that shows their ingenuity. We could observe from a questionnaire about the course that the students were interested in science and robots.","PeriodicalId":6585,"journal":{"name":"2013 Second International Conference on Robot, Vision and Signal Processing","volume":"11 1","pages":"229-233"},"PeriodicalIF":0.0,"publicationDate":"2013-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80060046","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}
With the improvement in technology of thin-film-transistor liquid-crystal display (TFT-LCD), the resolution requirement of display becomes higher and higher. Super-resolution algorithms are used to enlarge original low-resolution (LR) images to meet the visual quality of the high-resolution (HR) display. In this research, an efficient super resolution algorithm is proposed. The proposed algorithm consists of two steps. First, the Lanczos interpolation is used for LR images to get the preliminary HR images. For solving the over-smoothing problems generally caused by interpolation, it needs to add texture information to refine the preliminary HR images. Subsequently, a refinement process based on simple linear regression and the self-similarity between a pair of LR and HR images is performed to provide proper information of textures. In the experimental results, the proposed algorithm not only performs well in the objective measurement such as PSNR, but also in visual qualities.
{"title":"An Efficient Super Resolution Algorithm Using Simple Linear Regression","authors":"S. Tai, Tse-Ming Kuo, Kuo-Hao Li","doi":"10.1109/RVSP.2013.71","DOIUrl":"https://doi.org/10.1109/RVSP.2013.71","url":null,"abstract":"With the improvement in technology of thin-film-transistor liquid-crystal display (TFT-LCD), the resolution requirement of display becomes higher and higher. Super-resolution algorithms are used to enlarge original low-resolution (LR) images to meet the visual quality of the high-resolution (HR) display. In this research, an efficient super resolution algorithm is proposed. The proposed algorithm consists of two steps. First, the Lanczos interpolation is used for LR images to get the preliminary HR images. For solving the over-smoothing problems generally caused by interpolation, it needs to add texture information to refine the preliminary HR images. Subsequently, a refinement process based on simple linear regression and the self-similarity between a pair of LR and HR images is performed to provide proper information of textures. In the experimental results, the proposed algorithm not only performs well in the objective measurement such as PSNR, but also in visual qualities.","PeriodicalId":6585,"journal":{"name":"2013 Second International Conference on Robot, Vision and Signal Processing","volume":"45 1","pages":"287-290"},"PeriodicalIF":0.0,"publicationDate":"2013-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76829953","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}
An elaborated parallel implementation of particle filter in GPGPU has been applied to track steering hands of a car driver with depth image sensor for extracting arm and hand regions. Use of depth image sensor can provide more clear extraction of arm and hand regions for left and right than conventional image sensor. Parallel implementation in GPGPU allows fast computation and use of significantly larger number of particles in particle filter algorithm. Experimental results show computational performance of the proposed method.
{"title":"GPGPU Implementation for Steering Hands Tracking of a Car Driver by Particle Filter with Depth Image Sensor","authors":"N. Ikoma","doi":"10.1109/RVSP.2013.45","DOIUrl":"https://doi.org/10.1109/RVSP.2013.45","url":null,"abstract":"An elaborated parallel implementation of particle filter in GPGPU has been applied to track steering hands of a car driver with depth image sensor for extracting arm and hand regions. Use of depth image sensor can provide more clear extraction of arm and hand regions for left and right than conventional image sensor. Parallel implementation in GPGPU allows fast computation and use of significantly larger number of particles in particle filter algorithm. Experimental results show computational performance of the proposed method.","PeriodicalId":6585,"journal":{"name":"2013 Second International Conference on Robot, Vision and Signal Processing","volume":"7 1","pages":"164-167"},"PeriodicalIF":0.0,"publicationDate":"2013-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79021774","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}
Switching filter is a popular kind of image salt & pepper noise removal techniques in recent years. Unfortunately, noise detection schemes in existing switching filters are usually unsuitable for dealing with those images containing a certain number of noise-free pixels with gray levels 0s or 255s. To alleviate this issue, a new noise detection scheme is proposed, which can be regarded as a generalization of MDBUTMF's (modified decision based unsymmetric trimmed median filter) scheme. The proposed detection scheme innovatively utilizes image thresholding results obtained by gray level extremes 0 and 255 to further exclude fake noise pixels. And MDBUTMF's noise restoration scheme is adopted to restore our detected noise pixels. A series of simulations demonstrate that the proposed algorithm has higher noise detection accuracy and better restoration effect with higher PSNR values.
{"title":"Image Thresholding-Based Switching Filter for Salt & Pepper Noise Removal","authors":"Zuoyong Li, Kezong Tang, Zuchang Zhang","doi":"10.1109/RVSP.2013.13","DOIUrl":"https://doi.org/10.1109/RVSP.2013.13","url":null,"abstract":"Switching filter is a popular kind of image salt & pepper noise removal techniques in recent years. Unfortunately, noise detection schemes in existing switching filters are usually unsuitable for dealing with those images containing a certain number of noise-free pixels with gray levels 0s or 255s. To alleviate this issue, a new noise detection scheme is proposed, which can be regarded as a generalization of MDBUTMF's (modified decision based unsymmetric trimmed median filter) scheme. The proposed detection scheme innovatively utilizes image thresholding results obtained by gray level extremes 0 and 255 to further exclude fake noise pixels. And MDBUTMF's noise restoration scheme is adopted to restore our detected noise pixels. A series of simulations demonstrate that the proposed algorithm has higher noise detection accuracy and better restoration effect with higher PSNR values.","PeriodicalId":6585,"journal":{"name":"2013 Second International Conference on Robot, Vision and Signal Processing","volume":"1 1","pages":"21-24"},"PeriodicalIF":0.0,"publicationDate":"2013-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85479083","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}
This paper discussed the Interaction System with Robot Partner using Quantum-Inspired Bi-directional Associative Memory (QBAM). We have been developed QBAM which has the superior Memory Capacity and Recall Reliability compare with conventional models. Due to these advantages, the proposed system can be stored much information and its relationships. Using QBAM, we construct the interaction system that can be associated with gesture, object and voice information. In proposed system, Steady-state genetic algorithms are applied in order to detect objects via image processing. Spiking neural networks are applied to memorize the spatio-temporal patterns of gesture. For voice recognition, we use Julius that is open source large vocabulary continuous speech recognition engine. The results of experiment shows that proposed system is able to contribute for the facilitation of communication with Robot Partner.
{"title":"Human-Robot Interaction System with Quantum-Inspired Bidirectional Associative Memory","authors":"Naoki Masuyama, C. Loo, N. Kubota","doi":"10.1109/RVSP.2013.23","DOIUrl":"https://doi.org/10.1109/RVSP.2013.23","url":null,"abstract":"This paper discussed the Interaction System with Robot Partner using Quantum-Inspired Bi-directional Associative Memory (QBAM). We have been developed QBAM which has the superior Memory Capacity and Recall Reliability compare with conventional models. Due to these advantages, the proposed system can be stored much information and its relationships. Using QBAM, we construct the interaction system that can be associated with gesture, object and voice information. In proposed system, Steady-state genetic algorithms are applied in order to detect objects via image processing. Spiking neural networks are applied to memorize the spatio-temporal patterns of gesture. For voice recognition, we use Julius that is open source large vocabulary continuous speech recognition engine. The results of experiment shows that proposed system is able to contribute for the facilitation of communication with Robot Partner.","PeriodicalId":6585,"journal":{"name":"2013 Second International Conference on Robot, Vision and Signal Processing","volume":"50 1","pages":"66-71"},"PeriodicalIF":0.0,"publicationDate":"2013-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88723431","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}
The Cooperative Collision Avoidance Warning System (CCAWS) for vehicle safety in vehicular networks has become very important in recent years. However, the advanced positioning methods will affect the accuracy of the CCAWS warning information. Hence, we propose a self-correction of the vehicle-based positioning method in vehicular networks. Moreover, we design a dynamic vehicle full-view driver assistance system on the Android operating system for vehicular networks. The dynamic vehicle full-view driver assistance system can be shown on a monitor and the neighboring vehicles can also be drawn on the map. Users can easily understand the road conditions. Moreover, the application can exchange traffic information with other vehicles and the map can also show vehicles which are out of range. Furthermore, the application can show the time to collision between two vehicles.
{"title":"Dynamic Vehicle Full-View Driver Assistance System in Vehicular Networks","authors":"Tsung-Lin Wu, Chen-Da Tsai, Chao-Chun Yang","doi":"10.1109/RVSP.2013.17","DOIUrl":"https://doi.org/10.1109/RVSP.2013.17","url":null,"abstract":"The Cooperative Collision Avoidance Warning System (CCAWS) for vehicle safety in vehicular networks has become very important in recent years. However, the advanced positioning methods will affect the accuracy of the CCAWS warning information. Hence, we propose a self-correction of the vehicle-based positioning method in vehicular networks. Moreover, we design a dynamic vehicle full-view driver assistance system on the Android operating system for vehicular networks. The dynamic vehicle full-view driver assistance system can be shown on a monitor and the neighboring vehicles can also be drawn on the map. Users can easily understand the road conditions. Moreover, the application can exchange traffic information with other vehicles and the map can also show vehicles which are out of range. Furthermore, the application can show the time to collision between two vehicles.","PeriodicalId":6585,"journal":{"name":"2013 Second International Conference on Robot, Vision and Signal Processing","volume":"38 1","pages":"39-42"},"PeriodicalIF":0.0,"publicationDate":"2013-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78398691","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：