2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance最新文献_第4页

Visual Surveillance for Aircraft Activity Monitoring 用于飞机活动监测的视觉监视

2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance Pub Date : 2005-10-15 DOI: 10.1109/VSPETS.2005.1570923

D. Thirde, M. Borg, V. Valentin, F. Fusier, J. Aguilera, J. Ferryman, F. Brémond, M. Thonnat, M. Kampel

引用次数: 22

Towards intelligent camera networks: a virtual vision approach 迈向智能摄像头网络:一种虚拟视觉方法

2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance Pub Date : 2005-10-15 DOI: 10.1109/VSPETS.2005.1570913

F. Qureshi, Demetri Terzopoulos

{"title":"Towards intelligent camera networks: a virtual vision approach","authors":"F. Qureshi, Demetri Terzopoulos","doi":"10.1109/VSPETS.2005.1570913","DOIUrl":"https://doi.org/10.1109/VSPETS.2005.1570913","url":null,"abstract":"The goals of this paper are two-fold: (i) to present our initial efforts towards the realization of a fully autonomous sensor network of dynamic video cameras capable of providing perceptive coverage of a large public space, and (ii) to further the cause of exploiting visually and behaviorally realistic virtual environments in the development and testing of machine vision systems. In particular, our proposed sensor network employs techniques that enable a collection of active (pan-tilt-zoom) cameras to collaborate in performing various visual surveillance tasks, such as keeping one or more pedestrians within view, with minimal reliance on a human operator. The network features local and global autonomy and lacks any central controller, which entails robustness and scalability. Its functionality is the result of local decision-making capabilities at each camera node and communication between the nodes. We demonstrate our surveillance system in a virtual train station environment populated by autonomous, lifelike virtual pedestrians. Our readily reconfigurable virtual cameras generate synthetic video feeds that emulate those generated by real surveillance cameras monitoring public spaces. This type of research would be difficult in the real world given the costs of deploying and experimenting with an appropriately complex camera network in a large public space the size of a train station.","PeriodicalId":435841,"journal":{"name":"2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122604104","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: 32

Vehicle Class Recognition from Video-Based on 3D Curve Probes 基于三维曲线探针的视频车辆类别识别

2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance Pub Date : 2005-10-15 DOI: 10.1109/VSPETS.2005.1570927

Dongjin Han, Matthew J. Leotta, D. Cooper, J. Mundy

{"title":"Vehicle Class Recognition from Video-Based on 3D Curve Probes","authors":"Dongjin Han, Matthew J. Leotta, D. Cooper, J. Mundy","doi":"10.1109/VSPETS.2005.1570927","DOIUrl":"https://doi.org/10.1109/VSPETS.2005.1570927","url":null,"abstract":"A new approach is presented to vehicle-class recognition from a video clip. Two new concepts introduced are: probes consisting of local 3D curve-groups which when projected into video frames are features for recognizing vehicle classes in video clips; and Bayesian recognition based on class probability densities for groups of 3D distances between pairs of 3D probes. The most stable image features for vehicle class recognition appear to be image curves associate with 3D ridges on the vehicle surface. These ridges are mostly those occurring at metal/glass interfaces, two-surface intersections such as back and side, and self occluding contours such as wheel wells or vehicle-body apparent contours, i.e., silhouettes. There are other detectable surface curves, but most do not provide useful discriminatory features, and many of these are clutter, i.e., due to reflections from the somewhat shiny vehicle surface. Models are built and used for the considerable variability that exists in the features used. A Bayesian recognizer is then used for vehicle class recognition from a sequence of frames. The ultimate goal is a recognizer to deal with essentially all classes of civilian vehicles seen from arbitrary directions, at a broad range of distances and under the broad range of lighting ranging from sunny to cloudy. Experiments are run with a small set of classes to prove feasibility. This work uses estimated knowledge of the motion and position of the vehicle. We briefly indicate one way of inferring that information which uses ID projectivity invariance.","PeriodicalId":435841,"journal":{"name":"2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114465437","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: 35

Background initialization with a new robust statistical approach 一种新的鲁棒统计方法的后台初始化

2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance Pub Date : 2005-10-15 DOI: 10.1109/VSPETS.2005.1570910

Hanzi Wang, D. Suter

引用次数: 13

Modeling background from compressed video 从压缩视频建模背景

2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance Pub Date : 2005-10-15 DOI: 10.1109/VSPETS.2005.1570911

Weiqiang Wang, Datong Chen, Wen Gao, Jie Yang

引用次数: 23

Object Tracking using Color Correlogram 使用颜色相关图进行对象跟踪

2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance Pub Date : 2005-10-15 DOI: 10.1109/VSPETS.2005.1570924

Qi Zhao, Hai Tao

引用次数: 72

Tracking objects in occluding environments using temporal spatio-velocity transform 基于时空速度变换的遮挡环境中目标跟踪

2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance Pub Date : 2005-10-15 DOI: 10.1109/VSPETS.2005.1570902

K. Sato, J. Aggarwal

引用次数: 1

Efficient occlusion handling for multiple agent tracking by reasoning with surveillance event primitives 基于监视事件原语推理的多智能体跟踪的高效遮挡处理

2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance Pub Date : 2005-10-15 DOI: 10.1109/VSPETS.2005.1570897

P. Guha, A. Mukerjee, K. Venkatesh

{"title":"Efficient occlusion handling for multiple agent tracking by reasoning with surveillance event primitives","authors":"P. Guha, A. Mukerjee, K. Venkatesh","doi":"10.1109/VSPETS.2005.1570897","DOIUrl":"https://doi.org/10.1109/VSPETS.2005.1570897","url":null,"abstract":"Tracking multiple agents in a monocular visual surveillance system is often challenged by the phenomenon of occlusions. Agents entering the field of view can undergo two different forms of occlusions, either caused by crowding or due to obstructions by background objects at finite distances from the camera. The agents are primarily detected as foreground blobs and are characterized by their motion history and weighted color histograms. These features are further used for localizing them in subsequent frames through motion prediction assisted mean shift tracking. A number of Boolean predicates are evaluated based on the fractional overlaps between the localized regions and foreground blobs. We construct predicates describing a comprehensive set of possible surveillance event primitives including entry/exit, partial or complete occlusions by background objects, crowding, splitting of agents and algorithm failures resulting from track loss. Instantiation of these event primitives followed by selective feature updates enables us to develop an effective scheme for tracking multiple agents in relatively unconstrained environments.","PeriodicalId":435841,"journal":{"name":"2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131498386","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: 31

Object tracking with dynamic feature graph 基于动态特征图的目标跟踪

2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance Pub Date : 2005-10-15 DOI: 10.1109/VSPETS.2005.1570894

Feng Tang, Hai Tao

引用次数: 65

Can the Surveillance System Run Pose Variant Face Recognition in Real Time? 监控系统能否实时进行姿态变异人脸识别?

2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance Pub Date : 2005-10-15 DOI: 10.1109/VSPETS.2005.1570917

Hung-Son Le, Haibo Li

引用次数: 4