2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)最新文献_第4页

Optimal sensor placement for surveillance of large spaces 最佳传感器放置监视大空间

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289398

S. Indu, S. Chaudhury, Nikhil R. Mittal, A. Bhattacharyya

{"title":"Optimal sensor placement for surveillance of large spaces","authors":"S. Indu, S. Chaudhury, Nikhil R. Mittal, A. Bhattacharyya","doi":"10.1109/ICDSC.2009.5289398","DOIUrl":"https://doi.org/10.1109/ICDSC.2009.5289398","url":null,"abstract":"Visual sensor network design facilitates applications such as intelligent rooms, video surveillance, automatic multi-camera tracking, activity recognition etc. These applications require an efficient visual sensor layout which provides a minimum level of image quality or image resolution. This paper addresses the practical problem of optimally placing the multiple PTZ cameras to ensure maximum coverage of user defined priority areas with optimum values of parameters like pan, tilt, zoom and the locations of the cameras. The proposed algorithm works offline and does not require camera calibration. We mapped this problem as an optimization problem using Genetic Algorithm, by defining, coverage matrix as a set of sensor parameters and the space model parameters like priority areas, obstacles and feasible locations of the sensors, and by modelling discrete spaces using probabilistic frame work. We minimized the probability of occlusion due to randomly moving objects by covering each priority area using multiple cameras. The proposed method will be applicable for surveillance of large spaces with discrete priority areas like a hall with more than one entrance or many events happening at different locations in a hall eg.Casino. As we are optimizing the parameters like pan, tilt, zoom and even the locations of the cameras, the coverage provided by this approach will assure good resolution, which improves the QOS of the visual sensor network.","PeriodicalId":324810,"journal":{"name":"2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127079884","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: 50

Template matching based tracking of players in indoor team sports 基于模板匹配的室内团队运动运动员跟踪

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289408

E. Monier, P. Wilhelm, U. Rückert

引用次数: 12

PhD forum: A distributed architecture for object tracking across intelligent vision sensor network with constrained resources 博士论坛:资源受限的智能视觉传感器网络目标跟踪的分布式架构

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289388

J. Goshorn, R. Cruz, Serge J. Belongie

{"title":"PhD forum: A distributed architecture for object tracking across intelligent vision sensor network with constrained resources","authors":"J. Goshorn, R. Cruz, Serge J. Belongie","doi":"10.1109/ICDSC.2009.5289388","DOIUrl":"https://doi.org/10.1109/ICDSC.2009.5289388","url":null,"abstract":"Tracking objects across a network of intelligent vision sensors requires an architecture to distribute intelligent processing algorithms locally to the intelligent vision sensor and an algorithm for the communication of the acquired information to nearby sensors for collaboration and hand-offs of tracked objects. Additionally, the selection of which intelligent algorithms need to be performed at each intelligent sensor, and the management of constrained resources of the network, including network capacity (transmission rates), processing capacity (local processing power of sensor node) and in some cases, battery life of the sensor node must also occur. In the case of object tracking, as the number of tracked objects in the network increase, the resources consumed increases, as more processing power is required to create object descriptors and more networking resources are required to transmit information between sensors to collaboratively track the object. The local processing of intelligent vision algorithms at the vision node transforms high data-rate raw video data into low data rate features to be communicated across the network, thus relieving the networking capacity constraint. We focus on, what we view as the key resource, the sensor nodes' processing capacity, in creating a cluster-based distributed object tracking architecture, which includes resource management for processing capacities of the intelligent sensor nodes.","PeriodicalId":324810,"journal":{"name":"2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)","volume":"07 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129797557","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: 0

Resolution mosaic-based Smart Camera for video surveillance 基于马赛克分辨率的视频监控智能摄像头

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289364

M. A. Salem, Kristian Klaus, F. Winkler, B. Meffert

{"title":"Resolution mosaic-based Smart Camera for video surveillance","authors":"M. A. Salem, Kristian Klaus, F. Winkler, B. Meffert","doi":"10.1109/ICDSC.2009.5289364","DOIUrl":"https://doi.org/10.1109/ICDSC.2009.5289364","url":null,"abstract":"Video surveillance is one of the most data intensive applications. A typical video surveillance system consists of one or multiple video cameras, a central storage unit, and a central processing unit. At least two bottlenecks exist: First, the transmission capacity is limited, especially for raw data. Second, the central processing unit has to process the incoming data to give results in real time. Therefore, we propose an FPGA-based embedded camera system which performs all steps of image acquisition, region of interest extraction, generation of a multiresolution image, and image transmission. The proposed pipeline-based architecture allows a real time wavelet-based image segmentation and a detection of moving objects for surveillance purposes. The system is integrated in a single FPGA using external RAM as storage for images and for a Linux operating system which controls the data flow. With the pipeline concept and a Linux device driver it is possible to create a system for streaming the results of an image processing through a GbE interface. A real time processing is achieved. The camera transmits the captured images with 30 Mpixel/s, but the system is able to process 100 Mpixel/s.","PeriodicalId":324810,"journal":{"name":"2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121183967","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: 15

A distributed camera system for multi-resolution surveillance 用于多分辨率监控的分布式摄像系统

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289413

N. Bellotto, Eric Sommerlade, Ben Benfold, C. Bibby, I. Reid, D. Roth, Carles Fernández Tena, L. Gool, Jordi Gonzàlez

引用次数: 57

View-invariant full-body gesture recognition via multilinear analysis of voxel data 基于体素数据多线性分析的视不变全身手势识别

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289411

Bo Peng, G. Qian, Stjepan Rajko

引用次数: 26

Tracking in sparse multi-camera setups using stereo vision 使用立体视觉的稀疏多摄像机跟踪设置

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289371

G. Englebienne, T. V. Oosterhout, B. Kröse

{"title":"Tracking in sparse multi-camera setups using stereo vision","authors":"G. Englebienne, T. V. Oosterhout, B. Kröse","doi":"10.1109/ICDSC.2009.5289371","DOIUrl":"https://doi.org/10.1109/ICDSC.2009.5289371","url":null,"abstract":"Tracking with multiple cameras with nonoverlapping fields of view is challenging due to the differences in appearance that objects typically have when seen from different cameras. In this paper we use a probabilistic approach to track people across multiple, sparsely distributed cameras, where an observation corresponds to a person walking through the field of view of a camera. Modelling appearance and spatio-temporal aspects probabilistically allows us to deal with the uncertainty but, to obtain good results, it is important to maximise the information content of the features we extract from the raw video images. Occlusions and ambiguities within an observation result in noise, thus making the inference less confident. In this paper, we propose to position stereo cameras on the ceiling, facing straight down, thus greatly reducing the possibility of occlusions. This positioning also leads to specific requirements of the algorithms for feature extraction, however. Here, we show that depth information can be used to solve ambiguities and extract meaningful features, resulting in significant improvements in tracking accuracy.","PeriodicalId":324810,"journal":{"name":"2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128978457","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: 16

Multi-camera track-before-detect 多幅相机track-before-detect

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289405

M. Taj, A. Cavallaro

引用次数: 49

Face tracking and recognition by using omnidirectional sensor network 基于全向传感器网络的人脸跟踪与识别

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289367

Yuzuko Utsumi, Y. Iwai

引用次数: 2

Abnormal motion detection in a real-time smart camera system 实时智能摄像系统中的异常运动检测

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289359

Mona Akbarniai Tehrani, R. Kleihorst, Peter B. L. Meijer, L. Spaanenburg

引用次数: 10