Advanced Video and Signal Based Surveillance最新文献_第2页

AVSS 2011 demo session: Interactive person-retrieval in a distributed camera network AVSS 2011演示会议:分布式摄像机网络中的交互式人检索

Advanced Video and Signal Based Surveillance Pub Date : 2011-08-30 DOI: 10.1109/AVSS.2011.6027399

M. Bäuml, R. Stiefelhagen

引用次数: 0

AVSS2011 demo session: GPU enabled Smart Video Node AVSS2011演示会话:启用GPU的智能视频节点

Advanced Video and Signal Based Surveillance Pub Date : 2011-08-30 DOI: 10.1109/AVSS.2011.6027398

S. Guler, Jason A. Silverstein, Ian A. Pushee, Xiang Ma, Ashutosh Morde

引用次数: 1

AVSS 2011 demo session: Construction site monitoring from highly-overlapping MAV images AVSS 2011演示环节:从高度重叠的MAV图像监测建筑工地

Advanced Video and Signal Based Surveillance Pub Date : 2011-08-30 DOI: 10.1109/AVSS.2011.6027402

Stefan Kluckner, J. Birchbauer, C. Windisch, C. Hoppe, Arnold Irschara, Andreas Wendel, S. Zollmann, Gerhard Reitmayr, H. Bischof

引用次数: 10

AVSS 2011 demo session: OUTLIER - online learning and visualization of unusual events AVSS 2011演示会议:OUTLIER -在线学习和不寻常事件的可视化

Advanced Video and Signal Based Surveillance Pub Date : 2011-08-30 DOI: 10.1109/AVSS.2011.6027403

J. Birchbauer, S. Schulter, René Schuster, Georg Poier, M. Winter, P. Schallauer, P. Roth, H. Bischof

引用次数: 1

Pedestrian sensing for increased traffic safety and efficiency at signalized intersections 行人传感，提高交通安全和效率在信号交叉口

Advanced Video and Signal Based Surveillance Pub Date : 2011-08-30 DOI: 10.1109/AVSS.2011.6027406

W. Favoreel

引用次数: 4

AVSS 2011 demo session: Intelligent crossing sensor and vehicle detector AVSS 2011演示环节:智能交叉口传感器和车辆探测器

Advanced Video and Signal Based Surveillance Pub Date : 2011-08-30 DOI: 10.1109/AVSS.2011.6027404

M. Rosner

引用次数: 0

AVSS 2011 demo session AVSS 2011演示会议

Advanced Video and Signal Based Surveillance Pub Date : 2011-08-30 DOI: 10.1109/AVSS.2011.6027397

Frederic Garcia, B. Mirbach, Ángel Cuesta-Contreras

引用次数: 0

Issues in video analytics and surveillance systems: Research / prototyping vs. applications / user requirements 视频分析和监控系统中的问题:研究/原型vs.应用/用户需求

Advanced Video and Signal Based Surveillance Pub Date : 2007-09-05 DOI: 10.1109/AVSS.2007.4425278

Li-Qun Xu

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引用次数: 20

Computer-aided facial reconstruction using skulls 利用颅骨进行计算机辅助面部重建

Advanced Video and Signal Based Surveillance Pub Date : 2007-09-05 DOI: 10.1109/AVSS.2007.4425273

P. Tu

{"title":"Computer-aided facial reconstruction using skulls","authors":"P. Tu","doi":"10.1109/AVSS.2007.4425273","DOIUrl":"https://doi.org/10.1109/AVSS.2007.4425273","url":null,"abstract":"The ability to determine the identity of a skull found at a crime scene is of critical importance to the law enforcement community. Traditional clay-based methods attempt to reconstruct the face so as to enable identification of the deceased by members of the general public. However, these reconstructions lack consistency from practitioner to practitioner and it has been shown that the human recognition of these reconstructions against a photo gallery of potential victims is little better than chance. In this talk we discuss the automation of the reconstruction process. For a given skull, a data-driven 3D generative model of the face is constructed using a database of CT head scans. The reconstruction can be constrained based on prior knowledge such as age and or weight. To determine whether or not these reconstructions have merit, geometric methods for comparing reconstructions against a gallery of facial images are proposed. First, active appearance models are used to automatically detect a set of facial landmarks on each image. These landmarks are associated with 3D points on the reconstruction. Direct comparison of the reconstruction is problematic since in general the camera geometry used for image capture is unknown and there are uncertainties associated with the reconstruction and landmark detection processes. The first method of comparison uses constrained optimization to determine the optimal projection of the reconstruction on to the image. Residuals are then analyzed resulting in a ranking of the gallery. The second method uses boosting to learn which points are both reliable and discriminating. This results in a match/no-match classifier. Experimental evidence indicating that skull recognition from facial images can be achieved is presented.","PeriodicalId":332995,"journal":{"name":"Advanced Video and Signal Based Surveillance","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134540296","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: 1

Stereo vision and segmentation 立体视觉与分割

Advanced Video and Signal Based Surveillance Pub Date : 2007-09-05 DOI: 10.1109/AVSS.2007.4425274

A. Blake

引用次数: 1