Pub Date : 2012-12-01DOI: 10.1109/ICARCV.2012.6485409
Zhixin Yang, Difu Xiao
3D shape reuse, as an effective way to carry out innovative design, requires a digital model database where the entities are accurate and sufficient representations of objects in the real world. 3D scanning is a prevailing tool to quickly convert physical models into virtual ones. However, the scanned models without post-processing could not be used directly due to environment noise and accuracy limitation in terms of discrete sampling property in scanning. This paper introduces a systemic point-cloud de-noising and mesh smoothing method to handle this issue. The model de-noising and regularity is based on k-means clustering, and mesh smoothing module is an improved mean approach which processes the discrete data in the regular order. Case study will be given to verify the smoothing effectiveness. The proposed method could facilitate the construction of model database for design reuse, and could be output to downstream applications such as shape adaptive deformation, and shape searching.
{"title":"A systemic point-cloud de-noising and smoothing method for 3D shape reuse","authors":"Zhixin Yang, Difu Xiao","doi":"10.1109/ICARCV.2012.6485409","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485409","url":null,"abstract":"3D shape reuse, as an effective way to carry out innovative design, requires a digital model database where the entities are accurate and sufficient representations of objects in the real world. 3D scanning is a prevailing tool to quickly convert physical models into virtual ones. However, the scanned models without post-processing could not be used directly due to environment noise and accuracy limitation in terms of discrete sampling property in scanning. This paper introduces a systemic point-cloud de-noising and mesh smoothing method to handle this issue. The model de-noising and regularity is based on k-means clustering, and mesh smoothing module is an improved mean approach which processes the discrete data in the regular order. Case study will be given to verify the smoothing effectiveness. The proposed method could facilitate the construction of model database for design reuse, and could be output to downstream applications such as shape adaptive deformation, and shape searching.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123754307","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}
Pub Date : 2012-12-01DOI: 10.1109/ICARCV.2012.6485239
Maqbool Hussain, Muhammad Afzal, W. A. Khan, Sungyoung Lee
With the advent of smart technologies potential ideas have been emerged to facilitate human lives. Based on sensor technologies, smart homes concept is prevailing now a days that intends to bring tremendous changes in human lifestyle. The most prominent application is to equip the smart home with monitoring system that facilitate in managing care for elderly people. Elderly people with chronic disease need continuous care for managing their activities specially medications. The cost is increasing on care of elderly people and often needs sparing of family resource to take care during management of their activities and medications. This paper propose idea of Clinical Decision Support Service (CDSS) that provides guidelines and recommendation based on observed activities of patient. Our proposed CDSS service called Smart CDSS is deployed on platform that support various sensors and emotion recognition applications. The Smart CDSS knowledge base is currently supporting diabetes rules extracted from online resources and validated against recommendation from physician for 100 patients during their visits to local hospital. The Smart CDSS service allow interaction through standard base interfaces following HL7 vMR standard that allow seamless integration to underlying platform. Moreover, HL7 Arden Syntax is incorporated to scale up knowledge base for other diseases and allows sharing of clinician knowledge.
{"title":"Clinical Decision Support Service for elderly people in smart home environment","authors":"Maqbool Hussain, Muhammad Afzal, W. A. Khan, Sungyoung Lee","doi":"10.1109/ICARCV.2012.6485239","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485239","url":null,"abstract":"With the advent of smart technologies potential ideas have been emerged to facilitate human lives. Based on sensor technologies, smart homes concept is prevailing now a days that intends to bring tremendous changes in human lifestyle. The most prominent application is to equip the smart home with monitoring system that facilitate in managing care for elderly people. Elderly people with chronic disease need continuous care for managing their activities specially medications. The cost is increasing on care of elderly people and often needs sparing of family resource to take care during management of their activities and medications. This paper propose idea of Clinical Decision Support Service (CDSS) that provides guidelines and recommendation based on observed activities of patient. Our proposed CDSS service called Smart CDSS is deployed on platform that support various sensors and emotion recognition applications. The Smart CDSS knowledge base is currently supporting diabetes rules extracted from online resources and validated against recommendation from physician for 100 patients during their visits to local hospital. The Smart CDSS service allow interaction through standard base interfaces following HL7 vMR standard that allow seamless integration to underlying platform. Moreover, HL7 Arden Syntax is incorporated to scale up knowledge base for other diseases and allows sharing of clinician knowledge.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128514518","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}
Pub Date : 2012-12-01DOI: 10.1109/ICARCV.2012.6485293
Djamalladine Mahamat Pierre, M. N. Zakaria, A. J. Pal
The demand for Unmanned Aerial Vehicle (UAV) extends to various civil and military missions. While the use of remotely controlled UAV reduces the rate of human casualties in hazardous environments, it is reported that most of UAV accidents are caused by human factor errors. Automated path planning is required and because of the multi-objective nature of UAV's missions, several heuristic approaches to path planning have been proposed in order to automate UAV's navigation. While solving multi-objective problems requires the search for a set of pareto-optimal points, it requires the involvement of the user to select the desired result from the solution space. In this paper, we propose a variant of Self-Organizing Map approach to finding a compromised solution for a multi-objective path planning problem that does not require user involvement. Preliminary tests conducted in virtual environments have shown the immunity of our algorithm to local minima, and its efficiency to respond to multiple objectives.
{"title":"Self-Organizing Map approach to determining compromised solutions for multi-objective UAV path planning","authors":"Djamalladine Mahamat Pierre, M. N. Zakaria, A. J. Pal","doi":"10.1109/ICARCV.2012.6485293","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485293","url":null,"abstract":"The demand for Unmanned Aerial Vehicle (UAV) extends to various civil and military missions. While the use of remotely controlled UAV reduces the rate of human casualties in hazardous environments, it is reported that most of UAV accidents are caused by human factor errors. Automated path planning is required and because of the multi-objective nature of UAV's missions, several heuristic approaches to path planning have been proposed in order to automate UAV's navigation. While solving multi-objective problems requires the search for a set of pareto-optimal points, it requires the involvement of the user to select the desired result from the solution space. In this paper, we propose a variant of Self-Organizing Map approach to finding a compromised solution for a multi-objective path planning problem that does not require user involvement. Preliminary tests conducted in virtual environments have shown the immunity of our algorithm to local minima, and its efficiency to respond to multiple objectives.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130606255","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}
Pub Date : 2012-12-01DOI: 10.1109/ICARCV.2012.6485328
Mingyue Cui, Zhaojing Wu, Xue‐Jun Xie
This paper focuses on the problem of adaptive tracking for a class of stochastic mechanical control systems with unknown parameters. By reasonably introducing random noise, a method to construct stochastic Lagrangian control systems is given. Under some milder assumptions, an adaptive tracking controller is designed such that the mean square of the tracking error converges to an arbitrarily small neighborhood of zero by tuning design parameters.
{"title":"Adaptive tracking control for a class of stochastic mechanical systems","authors":"Mingyue Cui, Zhaojing Wu, Xue‐Jun Xie","doi":"10.1109/ICARCV.2012.6485328","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485328","url":null,"abstract":"This paper focuses on the problem of adaptive tracking for a class of stochastic mechanical control systems with unknown parameters. By reasonably introducing random noise, a method to construct stochastic Lagrangian control systems is given. Under some milder assumptions, an adaptive tracking controller is designed such that the mean square of the tracking error converges to an arbitrarily small neighborhood of zero by tuning design parameters.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129583685","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}
Pub Date : 2012-12-01DOI: 10.1109/ICARCV.2012.6485297
Guillaume Bresson, R. Aufrère, R. Chapuis
This paper presents a real-time Decentralized Monocular SLAM process. It is the first time, to our knowledge, that a decentralized SLAM with vehicles using only proprioceptive sensors and a single camera is presented. A new architecture has been built to cope with the problems involved by a decentralized scheme. A special care has been given to the data incest problem. It is solved thanks to a substate system. Network aspects and computational time are also considered. By using an Extended Kalman Filter and sending only essential information, we are able to make our decentralized algorithm suitable for an important number of vehicles. We also introduce a way to retrieve the distance between vehicles and so to put the different maps built in a common frame. This approach was tested using a realistic simulator with different trajectories.
{"title":"Real-time Decentralized Monocular SLAM","authors":"Guillaume Bresson, R. Aufrère, R. Chapuis","doi":"10.1109/ICARCV.2012.6485297","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485297","url":null,"abstract":"This paper presents a real-time Decentralized Monocular SLAM process. It is the first time, to our knowledge, that a decentralized SLAM with vehicles using only proprioceptive sensors and a single camera is presented. A new architecture has been built to cope with the problems involved by a decentralized scheme. A special care has been given to the data incest problem. It is solved thanks to a substate system. Network aspects and computational time are also considered. By using an Extended Kalman Filter and sending only essential information, we are able to make our decentralized algorithm suitable for an important number of vehicles. We also introduce a way to retrieve the distance between vehicles and so to put the different maps built in a common frame. This approach was tested using a realistic simulator with different trajectories.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130315985","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}
Pub Date : 2012-12-01DOI: 10.1109/ICARCV.2012.6485440
R. Cipolla
Summary form only given. The talk will begin with an overview of the state-of-the-art in the 3R's of computer vision: registration, reconstruction and recognition and will include demonstrations of research which has been recently commercialised at Cambrdige (Zappar, Metail, Toshiba gesture interfaces and Microsoft Kinect). This will be followed by a review of more advanced techniques in multi-view stereo and photometric stereo for recovering accurate and complete 3D models from uncalibrated images. I will then look in more detail at techniques for recovering the shape of deforming objects such as the human body and face and the challenges of large scale reconstruction of outdoor scenes and the application to ageing infrastructure.
{"title":"3D shape and its applications","authors":"R. Cipolla","doi":"10.1109/ICARCV.2012.6485440","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485440","url":null,"abstract":"Summary form only given. The talk will begin with an overview of the state-of-the-art in the 3R's of computer vision: registration, reconstruction and recognition and will include demonstrations of research which has been recently commercialised at Cambrdige (Zappar, Metail, Toshiba gesture interfaces and Microsoft Kinect). This will be followed by a review of more advanced techniques in multi-view stereo and photometric stereo for recovering accurate and complete 3D models from uncalibrated images. I will then look in more detail at techniques for recovering the shape of deforming objects such as the human body and face and the challenges of large scale reconstruction of outdoor scenes and the application to ageing infrastructure.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130839319","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}
Pub Date : 2012-12-01DOI: 10.1109/ICARCV.2012.6485302
Feng Su, G. Fang
Moving object identification and tracking by computer vision plays an important role in surveillance using mobile robots. In this paper, a new method for moving object tracking using an adaptive colour filter is introduced. This method is capable of identifying the most salient colour feature in the moving object and using this colour feature to track the object. This method is also capable of adapting this selected colour feature when the surrounding condition is changed. Experimental results have shown that the proposed method can perform robustly in tracking a moving object using a robot mounted camera in a crowded environment.
{"title":"Moving object tracking using an adaptive colour filter","authors":"Feng Su, G. Fang","doi":"10.1109/ICARCV.2012.6485302","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485302","url":null,"abstract":"Moving object identification and tracking by computer vision plays an important role in surveillance using mobile robots. In this paper, a new method for moving object tracking using an adaptive colour filter is introduced. This method is capable of identifying the most salient colour feature in the moving object and using this colour feature to track the object. This method is also capable of adapting this selected colour feature when the surrounding condition is changed. Experimental results have shown that the proposed method can perform robustly in tracking a moving object using a robot mounted camera in a crowded environment.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128867892","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}
Pub Date : 2012-12-01DOI: 10.1109/ICARCV.2012.6485140
Chang Wang, P. Wiggers, K. Hindriks, C. Jonker
We present a modified version of Extended Classifier System (XCS) on a humanoid NAO robot. The robot is capable of learning a complete, accurate, and maximally general map of an environment through evolutionary search and reinforcement learning. The standard alternation between explore and exploit trials is revised so that the robot relearns only when necessary. This modification makes the learning more effective and provides the XCS with external memory to evaluate the environmental change. Furthermore, it overcomes the drawbacks of learning rate settings in traditional XCS. A simple object seeking task is presented which demonstrates the desirable adaptivity of LCS for a sequential task on a real robot in dynamic environments.
{"title":"Learning Classifier System on a humanoid NAO robot in dynamic environments","authors":"Chang Wang, P. Wiggers, K. Hindriks, C. Jonker","doi":"10.1109/ICARCV.2012.6485140","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485140","url":null,"abstract":"We present a modified version of Extended Classifier System (XCS) on a humanoid NAO robot. The robot is capable of learning a complete, accurate, and maximally general map of an environment through evolutionary search and reinforcement learning. The standard alternation between explore and exploit trials is revised so that the robot relearns only when necessary. This modification makes the learning more effective and provides the XCS with external memory to evaluate the environmental change. Furthermore, it overcomes the drawbacks of learning rate settings in traditional XCS. A simple object seeking task is presented which demonstrates the desirable adaptivity of LCS for a sequential task on a real robot in dynamic environments.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128037517","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}
Pub Date : 2012-12-01DOI: 10.1109/ICARCV.2012.6485151
Yan Li, J. Wang, Size Xiao, Xiang Luo
This paper introduces a new algorithm for dead reckoning navigation named Constant Velocity Update (CUPT), which is an extension of popular Zero Velocity Update (ZUPT). With a low-cost IMU (Inertial Measurement Unit) attached to a user's shoe, the proposed algorithm can efficiently reduce IMU errors by detecting not only the stance phases during walking, but also the cases at constant velocity, such as in an elevator or on an escalator. The concept, design and test of a CUPT prototype are detailed in this paper. Test results show that it can effectively detect constant velocity, and its horizontal positioning errors are below 0.45% of the total distance travelled, and vertical errors below 0.25%. This performance reached the highest accuracy in available literature.
{"title":"Dead reckoning navigation with Constant Velocity Update (CUPT)","authors":"Yan Li, J. Wang, Size Xiao, Xiang Luo","doi":"10.1109/ICARCV.2012.6485151","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485151","url":null,"abstract":"This paper introduces a new algorithm for dead reckoning navigation named Constant Velocity Update (CUPT), which is an extension of popular Zero Velocity Update (ZUPT). With a low-cost IMU (Inertial Measurement Unit) attached to a user's shoe, the proposed algorithm can efficiently reduce IMU errors by detecting not only the stance phases during walking, but also the cases at constant velocity, such as in an elevator or on an escalator. The concept, design and test of a CUPT prototype are detailed in this paper. Test results show that it can effectively detect constant velocity, and its horizontal positioning errors are below 0.45% of the total distance travelled, and vertical errors below 0.25%. This performance reached the highest accuracy in available literature.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125663313","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}
Pub Date : 2012-12-01DOI: 10.1109/ICARCV.2012.6485186
Kai Zhan, F. Ramos, S. Faux
This paper proposes a novel activity recognition approach from video data obtained with a wearable camera. The objective is to recognise the user's activities from a tiny front-facing camera embedded in his/her glasses. Our system allows carers to remotely access the current status of a specified person, which can be broadly applied to those living with disabilities including the elderly who require cognitive assistance or guidance for daily activities. We collected, trained and tested our system on videos collected from different environmental settings. Sequences of four basic activities (drinking, walking, going upstairs and downstairs) are tested and evaluated in challenging real-world scenarios. An optical flow procedure is used as our primary feature extraction method, from which we downsize, reformat and classify sequence of activities using k-Nearest Neighbour algorithm (k-NN), LogitBoost (on Decision Stumps) and Support Vector Machine (SVM). We suggest the optimal settings of these classifiers through cross-validations and achieve an accuracy of 54.2% to 71.9%. Further smoothing using Hidden Markov Model (HMM) improves the result to 68.5%-82.1%.
本文提出了一种基于可穿戴摄像头视频数据的活动识别方法。目标是通过嵌入在用户眼镜中的微型前置摄像头识别用户的活动。我们的系统可让护理人员远距了解指定人士的现况，广泛适用于残疾人士，包括需要认知协助或日常活动指引的长者。我们收集、训练并测试了从不同环境中收集的视频系统。四种基本活动(喝酒、走路、上楼和下楼)的序列在具有挑战性的现实场景中进行测试和评估。使用光流过程作为我们的主要特征提取方法，从中我们使用k-最近邻算法(k-NN)， LogitBoost (on Decision Stumps)和支持向量机(SVM)缩小，重新格式化和分类活动序列。我们通过交叉验证提出了这些分类器的最佳设置，并实现了54.2%至71.9%的准确率。使用隐马尔可夫模型(HMM)进一步平滑将结果提高到68.5%-82.1%。
{"title":"Activity recognition from a wearable camera","authors":"Kai Zhan, F. Ramos, S. Faux","doi":"10.1109/ICARCV.2012.6485186","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485186","url":null,"abstract":"This paper proposes a novel activity recognition approach from video data obtained with a wearable camera. The objective is to recognise the user's activities from a tiny front-facing camera embedded in his/her glasses. Our system allows carers to remotely access the current status of a specified person, which can be broadly applied to those living with disabilities including the elderly who require cognitive assistance or guidance for daily activities. We collected, trained and tested our system on videos collected from different environmental settings. Sequences of four basic activities (drinking, walking, going upstairs and downstairs) are tested and evaluated in challenging real-world scenarios. An optical flow procedure is used as our primary feature extraction method, from which we downsize, reformat and classify sequence of activities using k-Nearest Neighbour algorithm (k-NN), LogitBoost (on Decision Stumps) and Support Vector Machine (SVM). We suggest the optimal settings of these classifiers through cross-validations and achieve an accuracy of 54.2% to 71.9%. Further smoothing using Hidden Markov Model (HMM) improves the result to 68.5%-82.1%.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126803574","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：