A new method with improved morphological operations on unstructured road is introduced in this paper. Mathematical morphology erosion and dilation operations are usually used so that the road and background are separated more clearly to acquire obvious road boundaries. How to use these operations reasonable will directly affect the subsequent detection. Firstly a binary image from an original image is segmented into the road and non-road regions by using 2-dimentional Otsu adaptive threshold segmentation algorithm. In terms of the feature of unstructured road, erosion operation is used twice and dilation operation is used once in this paper. Then, LOG operator is applied to detect edge. Finally, Hough transform is adopted to detect and mark the road boundaries. Experiments indicate that our method not only removes the unfavorable elements of non-road areas, but also has the advantages of fast operation and high accuracy.
{"title":"Research on unstructured road detection algorithm based on improved morphological operations","authors":"Xu Ming, Zhang Juan, Fang Zhijun","doi":"10.1049/CP.2017.0104","DOIUrl":"https://doi.org/10.1049/CP.2017.0104","url":null,"abstract":"A new method with improved morphological operations on unstructured road is introduced in this paper. Mathematical morphology erosion and dilation operations are usually used so that the road and background are separated more clearly to acquire obvious road boundaries. How to use these operations reasonable will directly affect the subsequent detection. Firstly a binary image from an original image is segmented into the road and non-road regions by using 2-dimentional Otsu adaptive threshold segmentation algorithm. In terms of the feature of unstructured road, erosion operation is used twice and dilation operation is used once in this paper. Then, LOG operator is applied to detect edge. Finally, Hough transform is adopted to detect and mark the road boundaries. Experiments indicate that our method not only removes the unfavorable elements of non-road areas, but also has the advantages of fast operation and high accuracy.","PeriodicalId":424212,"journal":{"name":"4th International Conference on Smart and Sustainable City (ICSSC 2017)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132084936","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 invention of the Microsoft Kinect sensor, high-resolution depth and visual sensing has become available for prevalent use in the smart home and medical rehabilitation. In this paper, we introduce an innovative approach for effective body movement tracking using Kinect Xbox 360 with a limited tracking system. A relatively scaled hand cursor mechanism is used for our system of interaction. Instead of tracking the whole body of the participant in the Kinect Depth space which produces 20 joints, we limit the tracking to only 2 joint (left and right hand) for the same action. Further, we have engaged Extended Kalman Filter to improve skeleton joint estimation which smooths the joint coordinates, placing the Z axis in a high level of calibration in order to make it work with X and Y coordinates simultaneously with a relatively high accuracy.
随着微软Kinect传感器的发明，高分辨率深度和视觉传感已经在智能家居和医疗康复中得到广泛应用。在本文中，我们介绍了一种利用Kinect Xbox 360有限跟踪系统进行有效身体运动跟踪的创新方法。我们的交互系统使用了一个相对缩放的手光标机制。比起在Kinect深度空间中追踪参与者的整个身体(游戏邦注:这会产生20个关节)，我们将同一动作的追踪限制为只有2个关节(左手和右手)。此外，我们还使用扩展卡尔曼滤波器来改进骨架关节估计，使关节坐标平滑，将Z轴置于高水平的校准中，以使其与X和Y坐标同时工作，具有相对较高的精度。
{"title":"A new approach for tracking human body movements by kinect sensor","authors":"Adjeisah Michael, Zhao Chen, Guohua Liu, Yang Yi","doi":"10.1049/CP.2017.0117","DOIUrl":"https://doi.org/10.1049/CP.2017.0117","url":null,"abstract":"With the invention of the Microsoft Kinect sensor, high-resolution depth and visual sensing has become available for prevalent use in the smart home and medical rehabilitation. In this paper, we introduce an innovative approach for effective body movement tracking using Kinect Xbox 360 with a limited tracking system. A relatively scaled hand cursor mechanism is used for our system of interaction. Instead of tracking the whole body of the participant in the Kinect Depth space which produces 20 joints, we limit the tracking to only 2 joint (left and right hand) for the same action. Further, we have engaged Extended Kalman Filter to improve skeleton joint estimation which smooths the joint coordinates, placing the Z axis in a high level of calibration in order to make it work with X and Y coordinates simultaneously with a relatively high accuracy.","PeriodicalId":424212,"journal":{"name":"4th International Conference on Smart and Sustainable City (ICSSC 2017)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121447661","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 proposes a Two-Column Convolutional Neural Network (TCCNN) to estimate the density and count of both sparse and highly dense crowd. The architecture of TCCNN derives from VGG-16 and Alexnet. We concatenate parts of these two networks to output the estimated density map and Gaussian Kernel is employed to generate the true density map as ground truth for training. Through integral on the entire density map, the number of people within the image can be obtained. We test the proposed method on such challenging datasets as UCF_CC_50, Shanghaitech and UCSD, to which different data augmenting methods are applied. The results show that our method is of competitive performance in comparison with other state of the art approaches.
{"title":"Crowd counting and density estimation via two-column convolutional neural network","authors":"Jianing Qiu, W. Wan, Hai-yan Yao, Kang Han","doi":"10.1049/CP.2017.0119","DOIUrl":"https://doi.org/10.1049/CP.2017.0119","url":null,"abstract":"This paper proposes a Two-Column Convolutional Neural Network (TCCNN) to estimate the density and count of both sparse and highly dense crowd. The architecture of TCCNN derives from VGG-16 and Alexnet. We concatenate parts of these two networks to output the estimated density map and Gaussian Kernel is employed to generate the true density map as ground truth for training. Through integral on the entire density map, the number of people within the image can be obtained. We test the proposed method on such challenging datasets as UCF_CC_50, Shanghaitech and UCSD, to which different data augmenting methods are applied. The results show that our method is of competitive performance in comparison with other state of the art approaches.","PeriodicalId":424212,"journal":{"name":"4th International Conference on Smart and Sustainable City (ICSSC 2017)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127036896","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 provides a method to predict 2D human pose in an image based on deep model ResNet-50. Human pose estimation is formulated as a regression problem towards body joints through top-down methods. First, we detect the position of humans in holistic image. Then, we take advantages of multi-stages cascade of ResNet-50 to reason about human body joints position. Our approach on challenging the FLIC datasets with large pose variation outperforms the state-of-the-art methods on these benchmarks.
{"title":"Human pose estimation via improved ResNet50","authors":"Xiao Xiao, W. Wan","doi":"10.1049/CP.2017.0126","DOIUrl":"https://doi.org/10.1049/CP.2017.0126","url":null,"abstract":"This paper provides a method to predict 2D human pose in an image based on deep model ResNet-50. Human pose estimation is formulated as a regression problem towards body joints through top-down methods. First, we detect the position of humans in holistic image. Then, we take advantages of multi-stages cascade of ResNet-50 to reason about human body joints position. Our approach on challenging the FLIC datasets with large pose variation outperforms the state-of-the-art methods on these benchmarks.","PeriodicalId":424212,"journal":{"name":"4th International Conference on Smart and Sustainable City (ICSSC 2017)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127548694","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 the last decade, mobile communications technologies has pervaded our society. In order to assess and analyze the location o f individuals and populations in this mobile world, mobile positioning or mobile telephone tracking is proposed as a monitoring tool to sense the movement o f people. In this paper, a monitoring tool called YouSense, a movement and behavior data collection mobile application, has been used. Our work mainly focus on YouSense GPS data cleaning, including filtering out wrong location information and filling the gaps when GPS is switched off. We set up several filter criteria for general YouSense GPS data cleaning through statistic analysis of different users' dataset. After data cleaning, we have also analyzed the location o f meaningful places for mobile users, such as home and work anchor points.
{"title":"GPS data cleaning and analysis based on YouSense mobile application","authors":"Qiyun Sun, R. Ahas, A. Aasa, W. Wan, Chi Yuan","doi":"10.1049/CP.2017.0113","DOIUrl":"https://doi.org/10.1049/CP.2017.0113","url":null,"abstract":"In the last decade, mobile communications technologies has pervaded our society. In order to assess and analyze the location o f individuals and populations in this mobile world, mobile positioning or mobile telephone tracking is proposed as a monitoring tool to sense the movement o f people. In this paper, a monitoring tool called YouSense, a movement and behavior data collection mobile application, has been used. Our work mainly focus on YouSense GPS data cleaning, including filtering out wrong location information and filling the gaps when GPS is switched off. We set up several filter criteria for general YouSense GPS data cleaning through statistic analysis of different users' dataset. After data cleaning, we have also analyzed the location o f meaningful places for mobile users, such as home and work anchor points.","PeriodicalId":424212,"journal":{"name":"4th International Conference on Smart and Sustainable City (ICSSC 2017)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121281301","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}
Technologies of identification by radio frequencies (RFID) contribute in many IOT application scenarios, such as healthcare systems and smart retails. This paper proposes a system for smart restaurant. In a four layered architecture the RFID technology is used to handle the order delivery activity. The protocol used is the hypertext transfer protocol (HTTP) and the application service relies on a representational state transfer (REST) web service. This system has been demonstrated to be realizable by some simulation using the Raspberry pi board and the ITEAD PN532 NFC module.
{"title":"IOT based smart restaurant system using RFID","authors":"B. E. Kossonon, Wang Ya","doi":"10.1049/CP.2017.0123","DOIUrl":"https://doi.org/10.1049/CP.2017.0123","url":null,"abstract":"Technologies of identification by radio frequencies (RFID) contribute in many IOT application scenarios, such as healthcare systems and smart retails. This paper proposes a system for smart restaurant. In a four layered architecture the RFID technology is used to handle the order delivery activity. The protocol used is the hypertext transfer protocol (HTTP) and the application service relies on a representational state transfer (REST) web service. This system has been demonstrated to be realizable by some simulation using the Raspberry pi board and the ITEAD PN532 NFC module.","PeriodicalId":424212,"journal":{"name":"4th International Conference on Smart and Sustainable City (ICSSC 2017)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128352337","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}
Secret sharing is crucial to information security in smart city related wireless applications. In this paper, we study how to optimally share secrets between two users using the effect of wireless channel dynamics on the data link layer. Specifically, we formulate an optimization problem whose objective is to minimize the expectation of the probability that an eavesdropper receives all secret sharing packets. Our contributions are: (i) we come up with the secret sharing mechanism that minimizes the aforementioned objective function and (ii) we perform analysis on our approach and derive the worst-case probability of the eavesdropper receiving all secret sharing packets. Our theoretical results are validated via simulations.
{"title":"Optimal secret sharing for secure wireless communications in the era of Internet of Things","authors":"Lei Miao, Dingde Jiang","doi":"10.1049/CP.2017.0122","DOIUrl":"https://doi.org/10.1049/CP.2017.0122","url":null,"abstract":"Secret sharing is crucial to information security in smart city related wireless applications. In this paper, we study how to optimally share secrets between two users using the effect of wireless channel dynamics on the data link layer. Specifically, we formulate an optimization problem whose objective is to minimize the expectation of the probability that an eavesdropper receives all secret sharing packets. Our contributions are: (i) we come up with the secret sharing mechanism that minimizes the aforementioned objective function and (ii) we perform analysis on our approach and derive the worst-case probability of the eavesdropper receiving all secret sharing packets. Our theoretical results are validated via simulations.","PeriodicalId":424212,"journal":{"name":"4th International Conference on Smart and Sustainable City (ICSSC 2017)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115251771","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 development and progress of science and technology, 3D model has been applied in many fields. The size and complexity of 3D model are huge, its transmission will be affected by the limited bandwidth. Therefore, it is necessary to compress the 3D model with the progressive compression technique and then display the model during the transmission process. The existing progressive compression algorithm rarely considers the attribute information, however, the attribute information often occupies much storage space. Therefore, we takes the triangular mesh model as the research object and proposes a progressive compression algorithm using the color attribute and material attribute. The 3D mesh model is simplified with geometric coding and attribute coding during the compression. Experimental results show that the algorithm can obtain a good model compression ratio and improve the processing speed of the model.
{"title":"3D model progressive compression algorithm using attributes","authors":"Yu-guo Dong, Xiaoging Yu, Pengfei Li","doi":"10.1049/CP.2017.0115","DOIUrl":"https://doi.org/10.1049/CP.2017.0115","url":null,"abstract":"With the development and progress of science and technology, 3D model has been applied in many fields. The size and complexity of 3D model are huge, its transmission will be affected by the limited bandwidth. Therefore, it is necessary to compress the 3D model with the progressive compression technique and then display the model during the transmission process. The existing progressive compression algorithm rarely considers the attribute information, however, the attribute information often occupies much storage space. Therefore, we takes the triangular mesh model as the research object and proposes a progressive compression algorithm using the color attribute and material attribute. The 3D mesh model is simplified with geometric coding and attribute coding during the compression. Experimental results show that the algorithm can obtain a good model compression ratio and improve the processing speed of the model.","PeriodicalId":424212,"journal":{"name":"4th International Conference on Smart and Sustainable City (ICSSC 2017)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122290787","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}
Small-sized loudspeakers due to high cutoff frequency, perform poor reproduction response, especially in low frequency. Traditional equalization methods for small-sized loudspeaker suffer from huge computational complexity when high accurate results are expected, which may lead to unacceptable time delay or pre-echo in reproduction sound. In this paper, instead of complicated low frequency equalization, virtual bass enhancement technology is introduced to restore low frequency auditory. In combination, SVD-Krylov algorithm is introduced to reduce loudspeaker model to promote the efficiency of high frequency equalization. Comparative experiments are presented and results show that the proposed approach can substantially reduce the time consumption without deterioration in accuracy of loudspeaker equalization.
{"title":"Small-sized loudspeaker equalization based SVD-Krylov model reduction and virtual bass enhancement","authors":"Yong Fang, Hecan Zou, Qinghua Huang","doi":"10.1049/CP.2017.0121","DOIUrl":"https://doi.org/10.1049/CP.2017.0121","url":null,"abstract":"Small-sized loudspeakers due to high cutoff frequency, perform poor reproduction response, especially in low frequency. Traditional equalization methods for small-sized loudspeaker suffer from huge computational complexity when high accurate results are expected, which may lead to unacceptable time delay or pre-echo in reproduction sound. In this paper, instead of complicated low frequency equalization, virtual bass enhancement technology is introduced to restore low frequency auditory. In combination, SVD-Krylov algorithm is introduced to reduce loudspeaker model to promote the efficiency of high frequency equalization. Comparative experiments are presented and results show that the proposed approach can substantially reduce the time consumption without deterioration in accuracy of loudspeaker equalization.","PeriodicalId":424212,"journal":{"name":"4th International Conference on Smart and Sustainable City (ICSSC 2017)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122979448","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}
A lot of research work has been carried out on the smart city and its applications in last two decades. Smart transportation is an application of smart city and also an important factor in building smart cities. Due to the complexity in passenger's traffic in big cities, a smart transportation system is needed to resolve the issue. This paper examines the concept of a vision-based transportation system to resolve the complexities in passenger's traffic and improving the productivity of existing transportation system. The vision-based transportation systems are expected to have positive mobility effects and be able to subsidize to the green environment by improving air quality and energy conservation for planning and developing a smart city. Thus, vision-based transportation is possibly an important approach for supporting and improving the transportation system. Vision-based transportation is a set of technologies applied to transportation infrastructure and vehicles to improve their performance. More specifically, vision-based transportation involves the application of established communications, controls, electronics, computer hardware, and software technologies in the transportation system. The paper examines in detail a broad range of vision-based transportation technologies and the expected benefits. These benefits include improved transportation system, travel time, throughput, cost savings, and most importantly safety and security. The paper considers a set of barriers that are required for the improvement of autonomous vehicles.
{"title":"Vision based autonomous vehicle for smart transportation system","authors":"Sagib Ali Haidery, M. Rizwan","doi":"10.1049/CP.2017.0111","DOIUrl":"https://doi.org/10.1049/CP.2017.0111","url":null,"abstract":"A lot of research work has been carried out on the smart city and its applications in last two decades. Smart transportation is an application of smart city and also an important factor in building smart cities. Due to the complexity in passenger's traffic in big cities, a smart transportation system is needed to resolve the issue. This paper examines the concept of a vision-based transportation system to resolve the complexities in passenger's traffic and improving the productivity of existing transportation system. The vision-based transportation systems are expected to have positive mobility effects and be able to subsidize to the green environment by improving air quality and energy conservation for planning and developing a smart city. Thus, vision-based transportation is possibly an important approach for supporting and improving the transportation system. Vision-based transportation is a set of technologies applied to transportation infrastructure and vehicles to improve their performance. More specifically, vision-based transportation involves the application of established communications, controls, electronics, computer hardware, and software technologies in the transportation system. The paper examines in detail a broad range of vision-based transportation technologies and the expected benefits. These benefits include improved transportation system, travel time, throughput, cost savings, and most importantly safety and security. The paper considers a set of barriers that are required for the improvement of autonomous vehicles.","PeriodicalId":424212,"journal":{"name":"4th International Conference on Smart and Sustainable City (ICSSC 2017)","volume":"9 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116781486","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}
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