2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)最新文献_第6页

Detection and recognition of sports(wo)men from multiple views 多角度对运动(女性)男性的检测与识别

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289407

Damien Delannay, Nicolas Danhier, C. Vleeschouwer

引用次数: 91

Efficient topology calibration and object tracking with distributed pan tilt cameras 分布式平移倾斜相机的高效拓扑标定和目标跟踪

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289360

N. Ukita, Kunihito Terashita, M. Kidode

{"title":"Efficient topology calibration and object tracking with distributed pan tilt cameras","authors":"N. Ukita, Kunihito Terashita, M. Kidode","doi":"10.1109/ICDSC.2009.5289360","DOIUrl":"https://doi.org/10.1109/ICDSC.2009.5289360","url":null,"abstract":"We propose a method for calibrating the topology of distributed pan tilt cameras (i.e., the structure of routes among FOVs) and its probabilistic model, which is useful for multi-object tracking in a wide area. To observe objects as long and many as possible, pan tilt control is an important issue in automatic calibration as well as in tracking. If only one object is observed by a camera and its neighboring cameras, the camera should point towards this object both in the calibration and tracking periods. However, if there are multiple objects, in the calibration period, the camera should be controlled towards an object that goes through an unreliable route in which a sufficient number of object detection results have not been observed. This control allows us to efficiently establish the reliable topology model. After the reliable topology model is established, on the other hand, the camera should be directed towards the route with the biggest possibility of object observation. We therefore propose a camera control framework based on the mixture of the reliability of the estimated routes and the probability of object observation. This framework is applicable both to camera calibration and object tracking by adjusting weight variables. Experiments demonstrate the efficiency of our camera control scheme for establishing the camera topology model and tracking objects as long as possible.","PeriodicalId":324810,"journal":{"name":"2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)","volume":"47 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":"129964283","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

A framework for determining overlap in large scale networks 确定大规模网络中重叠的框架

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289363

A. Hengel, Henry Detmold, Christopher S. Madden, A. Dick, Alex Cichowski, R. Hill

{"title":"A framework for determining overlap in large scale networks","authors":"A. Hengel, Henry Detmold, Christopher S. Madden, A. Dick, Alex Cichowski, R. Hill","doi":"10.1109/ICDSC.2009.5289363","DOIUrl":"https://doi.org/10.1109/ICDSC.2009.5289363","url":null,"abstract":"This paper presents a novel framework designed for calculating the topology of overlapping cameras in large surveillance systems. Such a framework is a key enabler for efficient network-wide surveillance, e.g. inter-camera tracking, especially in large surveillance networks. The framework presented can be adapted to utilise numerous contradiction and correlation approaches to identify overlapping portions of camera views using activity within the system. It can also utilise a various arbitrary occupancy cells which can be used to adjust both the memory requirements and accuracy of the topology generated. The framework is evaluated for its memory usage, processing speed and the accuracy of its overlap topology on a 26 camera dataset using various approaches. A further examination of memory requirements and processing speed on a larger 200 camera network is also presented. The results demonstrate that the framework significantly reduces memory requirements and improves execution speed whilst producing useful topologies from a large surveillance system at real-time speeds.","PeriodicalId":324810,"journal":{"name":"2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)","volume":"18 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":"114022464","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: 3

Covariance descriptors on moving regions for human detection in very complex outdoor scenes 基于协方差描述符的非常复杂户外场景中运动区域的人体检测

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289382

Giovanni Gualdi, A. Prati, R. Cucchiara

{"title":"Covariance descriptors on moving regions for human detection in very complex outdoor scenes","authors":"Giovanni Gualdi, A. Prati, R. Cucchiara","doi":"10.1109/ICDSC.2009.5289382","DOIUrl":"https://doi.org/10.1109/ICDSC.2009.5289382","url":null,"abstract":"The detection of humans in very complex scenes can be very challenging, due to the performance degradation of classical motion detection and tracking approaches. An alternative approach is the detection of human-like patterns over the whole image. The present paper follows this line by extending Tuzel et al.'s technique [1] based on covariance descriptors and LogitBoost algorithm applied over Riemannian manifolds. Our proposal represents a significant extension of it by: (a) exploiting motion information to focus the attention over areas where motion is present or was present in the recent past; (b) enriching the human classifier by additional, dedicated cascades trained on positive and negative samples taken from the specific scene; (c) using a rough estimation of the scene perspective, to reduce false detections and improve system performance. This approach is suitable in multi-camera scenarios, since the monolithic block for human-detection remains the same for the whole system, whereas the parameter tuning and set-up of the three proposed extensions (the only camera-dependent parts of the system), are automatically computed for each camera. The approach has been tested on a construction working site where complexity and dynamics are very high, making human detection a real challenge. The experimental results demonstrate the improvements achieved by the proposed approach.","PeriodicalId":324810,"journal":{"name":"2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)","volume":"58 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":"126659505","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

3D localization of projected objects for surveillance 用于监视的投影对象的3D定位

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289369

Sunghoon Jung, Do-won Jang, Minhwan Kim

引用次数: 5

Dependable integrated surveillance systems for the physical security of metro railways 可靠的综合监控系统，为地铁的物理安全

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289385

G. Bocchetti, Francesco Flammini, Concetta Pragliola, Alfio Pappalardo

{"title":"Dependable integrated surveillance systems for the physical security of metro railways","authors":"G. Bocchetti, Francesco Flammini, Concetta Pragliola, Alfio Pappalardo","doi":"10.1109/ICDSC.2009.5289385","DOIUrl":"https://doi.org/10.1109/ICDSC.2009.5289385","url":null,"abstract":"Rail-based mass transit systems are vulnerable to many criminal acts, ranging from vandalism to terrorism. In this paper, we present the architecture, the main functionalities and the dependability related issues of a security system specifically tailored to metro railways. Heterogeneous intrusion detection, access control, intelligent video-surveillance and sound detection devices are integrated in a cohesive Security Management System (SMS). In case of emergencies, the procedural actions required to the operators involved are orchestrated by the SMS. Redundancy both in sensor dislocation and hardware apparels (e.g. by local or geographical clustering) improve detection reliability, through alarm correlation, and overall system resiliency against both random and malicious threats. Video-analytics is essential, since a small number of operators would be unable to visually control a large number of cameras. Therefore, the visualization of video streams is activated automatically when an alarm is generated by smart-cameras or other sensors, according to an event-driven approach. The system is able to protect stations (accesses, technical rooms, platforms, etc.), tunnels (portals, ventilation shafts, etc.), trains and depots. Presently, the system is being installed in the Metrocampania underground regional railway. To the best of our knowledge, this is the first subway security system featuring artificial intelligence algorithms both for video and audio surveillance. The security system is highly heterogeneous in terms not only of detection technologies but also of embedded computing power and communication facilities. In fact, sensors can differ in their inner hardware-software architecture and thus in the capacity of providing information security and dependability. The focus of this paper is on the development of novel solutions to achieve a measurable level of dependability for the security system in order to fulfill the requirements of the specific application.","PeriodicalId":324810,"journal":{"name":"2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)","volume":"9 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":"128955310","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: 51

Multi-camera tracking on a graph using Markov chain Monte Carlo 用马尔科夫链蒙特卡罗实现多摄像机跟踪图

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289352

Honggab Kim, J. Romberg, W. Wolf

{"title":"Multi-camera tracking on a graph using Markov chain Monte Carlo","authors":"Honggab Kim, J. Romberg, W. Wolf","doi":"10.1109/ICDSC.2009.5289352","DOIUrl":"https://doi.org/10.1109/ICDSC.2009.5289352","url":null,"abstract":"Wide-area surveillance requires a system of multiple cameras that are sparsely distributed without overlapping fields of view. Tracking objects in such a setting is challenging because blind gaps between disjoint camera views cannot ensure spatial, temporal, and visual continuity in successive observations. We propose an association algorithm for tracking an unknown number of objects with sparsely distributed uncalibrated cameras. To model traffic patterns in a monitored environment, we exploit the statistics on overall traffic and the probabilistic dependence of a path in one camera view on the previous path in another camera view. The dependency and the frequency of allowable paths are represented in a graph model. Without using a high-order transition model, the proposed graph disambiguates traffic patterns and generalizes traffic constraints in motorway and indoor scenarios. Based on the graph model, we derive a posterior probability of underlying paths, given a set of observations. The posterior evaluates not only the plausibility of individual paths but also the hypothesized number of paths with respect to traffic statistics of the environment. To find the maximum a posteriori, we use Markov chain Monte Carlo (MCMC). In contrast to other MCMC-based tracking methods, the proposed MCMC sampling requires neither additional cost to compute an initial sample nor information about the number of objects passing through the environment.","PeriodicalId":324810,"journal":{"name":"2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)","volume":"43 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":"122663826","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: 40

Redundancy removal through semantic neighbor selection in Visual Sensor Networks 基于语义邻居选择的视觉传感器网络冗余去除

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289402

Yang Bai, H. Qi

{"title":"Redundancy removal through semantic neighbor selection in Visual Sensor Networks","authors":"Yang Bai, H. Qi","doi":"10.1109/ICDSC.2009.5289402","DOIUrl":"https://doi.org/10.1109/ICDSC.2009.5289402","url":null,"abstract":"Sensor networks utilize a large number of sensing nodes powered by on-board batteries for much improved surveillance quality. Due to the random and dense sensor deployment, when the entire target area is at k-coverage, a significant portion of it will be covered by more than k sensors. The neighbor selection scheme could find those redundant sensors and put them into the sleep mode for energy conservation purpose, thus prolonging the network lifetime. Depending on the type of sensing modalities used in the network, the neighbor selection method can be very different. Most conventional sensor networks adopt scalar sensors with omni-directional sensing capability and thus the neighborhood depends only on the distance between sensors. The focus of this paper is on neighbor selection in Visual Sensor Networks (VSNs) that consist of a large number of imaging sensors where directional sensing is adopted. Therefore, the neighborhood depends not only on the distance, but also on their orientations and occlusion conditions. In this paper we present a semantic neighbor selection algorithm for VSNs where the semantic neighbor is defined as a group of geographically close visual sensors that capture the same or similar scene. Our semantic neighbor selection is based on the principle of image comparison by using effective feature extraction approach that is both compact and with high accuracy. We develop a so-called Extend Speeded-UP Robust Features (E-SURF) based on two popularly used feature extraction schemes, SURF and SIFT. The E-SURF feature is more compact than SIFT in terms of data volume so that the semantic neighbor selection process would not incur a heavy overhead in communication. It is also more accurate than SURF in terms of finding the right neighbors. To ensure this scheme works well in practical VSNs, we present a protocol design for implementation.","PeriodicalId":324810,"journal":{"name":"2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)","volume":"13 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":"124291252","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

Robust construction of the Camera Network Complex for topology recovery 用于拓扑恢复的摄像机网络复合体的鲁棒构造

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289401

E. Lobaton, Ramanarayan Vasudevan, S. Sastry, R. Bajcsy

{"title":"Robust construction of the Camera Network Complex for topology recovery","authors":"E. Lobaton, Ramanarayan Vasudevan, S. Sastry, R. Bajcsy","doi":"10.1109/ICDSC.2009.5289401","DOIUrl":"https://doi.org/10.1109/ICDSC.2009.5289401","url":null,"abstract":"While performing tasks such as estimating the topology of camera network coverage or coordinate-free object tracking and navigation, knowledge of camera position and other geometric constraints about the environment are considered unnecessary. Instead, topological information captured by the construction of a simplicial representation called the CN-Complex can be utilized to perform these tasks. This representation can be thought of as a generalization of the so-called vision graph of a camera network. The construction of this simplicial complex consists of two steps: the decomposition of the camera coverage through the detection of occlusion events, and the discovery of overlapping areas between the multiple decomposed regions. In this paper, we present an algorithm for performing both of these tasks in the presence of multiple targets and noisy observations. The algorithm exploits temporal correlations of the detections to estimate probabilities of overlap in a distributed manner. No correspondence, appearance models, or tracking are utilized. Instead of applying a single threshold on the probabilities, we analyze the persistence of the topological features in our representation through a filtration process. We demonstrate the validity of our approach through simulation and an experimental setup.","PeriodicalId":324810,"journal":{"name":"2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)","volume":"31 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":"121623852","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: 2

Continuously evolvable Bayesian Nets for human action analysis in videos 视频中人类行为分析的连续进化贝叶斯网络

2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC) Pub Date : 2009-10-20 DOI: 10.1109/ICDSC.2009.5289386

Nirmalya Ghosh, B. Bhanu, Giovanni Denina

引用次数: 2