2012 19th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)最新文献

Computational intelligence for advanced manufacturing system management: A review 先进制造系统管理的计算智能研究进展

2012 19th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) Pub Date : 2012-11-01 DOI: 10.1504/IJISTA.2014.068828

L. Butler, G. Bright

引用次数: 0

Motion periodicity based pedestrian detection and particle filter based pedestrian tracking using stereo vision camera 基于运动周期的行人检测和基于粒子滤波的立体视觉摄像机行人跟踪

2012 19th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) Pub Date : 2012-11-01 DOI: 10.1504/IJCAT.2014.063913

K. Mutib, M. Emaduddin, M. Alsulaiman, R. Hedjar, E. Mattar

{"title":"Motion periodicity based pedestrian detection and particle filter based pedestrian tracking using stereo vision camera","authors":"K. Mutib, M. Emaduddin, M. Alsulaiman, R. Hedjar, E. Mattar","doi":"10.1504/IJCAT.2014.063913","DOIUrl":"https://doi.org/10.1504/IJCAT.2014.063913","url":null,"abstract":"A novel method is proposed that adapts a previously proposed LADAR based pedestrian detection and tracking technique by introducing a stereo-vision based segmentation technique for the purpose of pedestrian detection and tracking. The proposed method detects the harmonic motions of limbs and body during a typical human walk and temporally propagates the position, stride, direction and phase using a particle filter. The particle-filter uses a human limb-motion model and is able to track the walking pedestrians in a heavily occluded environment. Potential 3D point clusters belonging to arms and feet are extracted employing an adapted version of RANSAC based segmentation algorithm. A Fourier-transform based periodogram confirms the periodicity for each point-cluster representing limbs. Since RGB or intensity data from the stereo-vision input is ignored and the proposed method completely relies upon 3D data produced by the stereo-vision sensor, reliable illumination invariant pedestrian detection and tracking results are achieved using Daimler-Stereo-Pedestrian-Detection-Dataset. Further lab experiments also confirm the viability of the method within the indoor environment.","PeriodicalId":328187,"journal":{"name":"2012 19th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121673836","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: 13

Steering coordination control of front wheels for a four in-wheel-motor drive electric vehicle 四轮电机驱动电动汽车前轮转向协调控制

2012 19th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) Pub Date : 2012-11-01 DOI: 10.1504/IJBBR.2013.058722

X. Zhu, H. Qiu, Z. Dong, Z. Qi, Y. Zhang

引用次数: 3

Monitoring and remote sensing of the street lighting system using computer vision and image processing techniques for the purpose of mechanized blackouts 利用计算机视觉和图像处理技术对街道照明系统进行监测和遥感，以实现机械化停电

2012 19th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) Pub Date : 2012-11-01 DOI: 10.1049/CP.2013.1016

P. N. Zanjani, V. Ghods, M. Bahadori

{"title":"Monitoring and remote sensing of the street lighting system using computer vision and image processing techniques for the purpose of mechanized blackouts","authors":"P. N. Zanjani, V. Ghods, M. Bahadori","doi":"10.1049/CP.2013.1016","DOIUrl":"https://doi.org/10.1049/CP.2013.1016","url":null,"abstract":"Street lighting system as one of the foremost facilities used in the cities plays a pivotal role in reducing nocturnal car accidents and enhancing individual and social security. Therefore, one of the main priorities in Electrical Distribution Companies is the timely repair and maintenance of the street lightening which should be regularly checked. The common mechanized monitoring of the street lighting is based on measuring the consumed current of each lamp and comparing it with the lamp nominal current. In this way, the error in network is identified. Monitoring street lighting in Iran is presently conducted by traditional inspection and check-out method. This paper suggests a new method for monitoring and remote sensing of the street lighting system which is completely isolated from electricity network and applies picture shooting of the street lighting network, image processing, and computer vision techniques and separating the light source method in the picture. The system performance was simulated and verified by MATLAB software. The results indicate the ability and effectiveness of this method and led to closing a research contract with Tehran Electrical Distribution Company for pilot implementation of the plan in one of the passageways in Tehran.","PeriodicalId":328187,"journal":{"name":"2012 19th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121435215","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: 26

Recursive Gauss-Newton based training algorithm for neural network modelling of an unmanned helicopter dynamics 基于递归高斯-牛顿的无人直升机动力学神经网络建模训练算法

2012 19th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) Pub Date : 2012-11-01 DOI: 10.1504/IJISTA.2014.059300

S. S. Shamsudin, Xiaoqi Chen

引用次数: 2

A novel control method for electric power steering system based on dead-zone Inverse Transforming Compensation in a four-in-wheel-motor drive Electric Vehicle 基于死区逆变换补偿的四轮电动汽车电动助力转向系统控制新方法

2012 19th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) Pub Date : 2012-11-01 DOI: 10.1504/IJBBR.2013.058720

S. Liang, Z. Qi, Z. Dong, H. Qiu, S. Hu

引用次数: 0

Extension of automated melanoma screening for non-melanocytic skin lesions 扩展非黑素细胞性皮肤病变的黑色素瘤自动筛查

2012 19th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) Pub Date : 2012-11-01 DOI: 10.1504/IJCAT.2014.063914

Kouhei Shimizu, H. Iyatomi, K. Norton, M. E. Celebi

{"title":"Extension of automated melanoma screening for non-melanocytic skin lesions","authors":"Kouhei Shimizu, H. Iyatomi, K. Norton, M. E. Celebi","doi":"10.1504/IJCAT.2014.063914","DOIUrl":"https://doi.org/10.1504/IJCAT.2014.063914","url":null,"abstract":"In this paper, we present an automated melanoma screening system that supports not only melanocytic skin lesions (MSLs) but also non-melanocytic skin lesions (NoMSLs). Melanoma is known as the most fatal skin cancer. Therefore, early detection is highly desired. However, melanoma diagnosis is not easy even for expert dermatologists. In such a background, several researchers have developed automated methods for melanoma detection but they mostly focused only on MSLs while NoMSLs have been almost neglected. To expand the scope to NoMSLs, we developed two melanoma classification models, namely the single-shot and the double-shot. The single-shot model differentiates melanomas from all the other skin lesions including NoMSLs. The double-shot model divides the task into two subtasks. Firstly, it differentiates MSLs from NoMSLs and then differentiates melanomas from the other MSLs. The single-shot achieved a sensitivity (SE) of 92.9% and a specificity (SP) of 83.9%, while the double-shot achieved an SE of 97.6% and an SP of 92.2% when 10 image features were used. The double-shot showed superior detection performance to the single-shot except when their constituent image features were limited.","PeriodicalId":328187,"journal":{"name":"2012 19th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114504358","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

Spatiotemporal volume video event detection for fault monitoring in assembly automation 装配自动化故障监测的时空体视频事件检测

2012 19th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) Pub Date : 2012-11-01 DOI: 10.1504/IJISTA.2014.059302

Kevin Hughes, Heshan A. Fernando, Greg Szkilnyk, B. Surgenor, M. Greenspan

{"title":"Spatiotemporal volume video event detection for fault monitoring in assembly automation","authors":"Kevin Hughes, Heshan A. Fernando, Greg Szkilnyk, B. Surgenor, M. Greenspan","doi":"10.1504/IJISTA.2014.059302","DOIUrl":"https://doi.org/10.1504/IJISTA.2014.059302","url":null,"abstract":"A major goal of many manufacturers is to minimize production downtime caused by machine faults and equipment breakdowns. This goal is typically achieved using sensor-based systems that can quickly detect and diagnose machine faults of various types. This paper proposes the use of a video event detection method based on spatiotemporal volumes (STVs) in a fault monitoring application to complement and improve upon existing systems. To detect faults, a set of image sequences are captured using a single web cam from the part dispensing region of an assembly machine testbed. The motion is segmented in each image creating binary frames which are stacked to build a STV. Normal operation of the machine is modeled by building a STV from several training sequences. New STVs are compared to the model and classified as either normal or faulty behaviour based on a calculated similarity measure. Both full-STV and partial-STV matching methods are tested. Test results show that the system is very effective on the data set collected. Recommendations for further exploration of this concept are made that include alternative video event detection techniques and different testbeds.","PeriodicalId":328187,"journal":{"name":"2012 19th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133545029","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: 7

A road surface identification method for a four in-wheel-motor drive electric vehicle 一种四轮电机驱动电动汽车路面识别方法

2012 19th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) Pub Date : 2012-11-01 DOI: 10.1504/IJBBR.2013.058721

Z. Deng, Z. Qi, Z. Dong, P. He, C. Han, S. Ren

引用次数: 4