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2006 IEEE International Conference on Video and Signal Based Surveillance最新文献

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Principal Component Analysis of Multi-view Images for Viewpoint-Independent Face Recognition 非视点人脸识别中的多视点图像主成分分析
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.93
Takio Kurita, Tatsuya Hosoi, Akinori Hidaka
{"title":"Principal Component Analysis of Multi-view Images for Viewpoint-Independent Face Recognition","authors":"Takio Kurita, Tatsuya Hosoi, Akinori Hidaka","doi":"10.1109/AVSS.2006.93","DOIUrl":"https://doi.org/10.1109/AVSS.2006.93","url":null,"abstract":"We consider the problem of recognizing a specific human face in different poses (viewing direction) when only one frontal face image exists in the face database. To solve this problem, prior knowledge is learned by using principal component analysis on a set of multi-view images to obtain aligned principal components. They are used together with the idea of linear object classes to synthesize a virtual view of the frontal face from a given face image taken from a different viewing direction. The estimated virtual frontal view is then compared with the stored frontal face images in the face database to identify the person. Experimental results are shown using face images captured from different viewpoints.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"405 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127244074","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
On Optimisation of Smart Card Face Verification Systems 智能卡人脸验证系统的优化研究
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.85
T. Bourlai, J. Kittler, K. Messer
{"title":"On Optimisation of Smart Card Face Verification Systems","authors":"T. Bourlai, J. Kittler, K. Messer","doi":"10.1109/AVSS.2006.85","DOIUrl":"https://doi.org/10.1109/AVSS.2006.85","url":null,"abstract":"The optimisation of a smart card face verification system (SCFVS) design is a complex task. As the parameters involved are not independent, the search space is of exponential complexity. We investigate simplified optimisation strategies and demonstrate that both system performance and speed of access can be improved by jointly optimised parameter setting and level of probe compression. Experimental results suggest that the choice of one strategy over another is a matter of the amount of time available for the system design, system performance and response time.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123897034","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
The Audio Surveillance Eye 音频监控之眼
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.112
H. Alghassi, S. Tafazoli, P. Lawrence
{"title":"The Audio Surveillance Eye","authors":"H. Alghassi, S. Tafazoli, P. Lawrence","doi":"10.1109/AVSS.2006.112","DOIUrl":"https://doi.org/10.1109/AVSS.2006.112","url":null,"abstract":"In this paper we present a novel signal processing algorithm accompanied with an array structure for audio signal localization and surveillance in three dimensional space. This method, which has similarities to the eye structure, consists of a novel hemispherical microphone array with microphones on the shell and one microphone in the sphere center. A signal processing scheme utilizes parallel creation of a special closeness function for each microphone direction on the shell. Contrary to traditional algorithmic sound source localization techniques, our method is based on some simple parallel mathematical calculations in the time domain; therefore it can be easily implemented on a custom designed integrated circuit.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123632564","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: 10
A Knowledge-Based Approach for Detecting Unattended Packages in Surveillance Video 基于知识的监控视频中无人值守包裹检测方法
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.6
Sijun Lu, Jian Zhang, D. Feng
{"title":"A Knowledge-Based Approach for Detecting Unattended Packages in Surveillance Video","authors":"Sijun Lu, Jian Zhang, D. Feng","doi":"10.1109/AVSS.2006.6","DOIUrl":"https://doi.org/10.1109/AVSS.2006.6","url":null,"abstract":"This paper describes a novel approach for detecting unattended packages in surveillance video. Unlike the traditional approach to just detecting stationary objects in monitored scenes, our approach detects unattended packages based on accumulated knowledge about human and non-human objects from continuous object tracking and classification. We design different reasoning rules for detecting different scenarios of the unattended package events. In the case where a package is left unattended by a single person explicitly, a rule using human activity recognition is introduced to decide the package ownership. In the case where a suspicious package is dropped down by a group of humans or under heavy occlusions, a rule based on historic tracking and classification information is proposed. Furthermore, an additional rule is given to reduce false alarms that may happen with traditional stationary object detection methods.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127471132","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: 22
Learning Foveal Sensing Strategies in Unconstrained Surveillance Environments 无约束监视环境下中央凹感知策略的学习
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.72
Andrew D. Bagdanov, A. Bimbo, W. Nunziati, F. Pernici
{"title":"Learning Foveal Sensing Strategies in Unconstrained Surveillance Environments","authors":"Andrew D. Bagdanov, A. Bimbo, W. Nunziati, F. Pernici","doi":"10.1109/AVSS.2006.72","DOIUrl":"https://doi.org/10.1109/AVSS.2006.72","url":null,"abstract":"In this paper we report on techniques for automatically learning foveal sensing strategies for an active pan-tiltzoom camera. The approach uses reinforcement learning to discover foveal actions maximizing the performance of visual detectors, that are in turn assumed to be highly correlated with the task at hand. In our case, the main goal is to recognize people, hence a frontal face detection module is employed. The system uses reinforcement learning to learn if, when and how to foveate on a subject, based on its previous experience in terms or successful actions in similar situations. An action is successful if it leads to a correct face detection in the high resolution images obtained when the subject is zoomed in. In contrast with existing methods, the proposed approach obviates the need for camera calibration and camera performance modeling. Also, the method does not rely on active tracking of targets. Experimental results show how the system is capable of learning foveation strategies without requiring extensive a priori information or environmental models. Results also illustrate how the system effectively learns a strategy that allows the camera to foveate only in situations where successful detection is highly likely.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121543282","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
An Abandoned/Removed Objects Detection Algorithm and Its Evaluation on PETS Datasets 一种基于pet数据集的废弃/移除目标检测算法及其评价
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.18
P. Spagnolo, Andrea Caroppo, M. Leo, Tommaso Martiriggiano, T. D’orazio
{"title":"An Abandoned/Removed Objects Detection Algorithm and Its Evaluation on PETS Datasets","authors":"P. Spagnolo, Andrea Caroppo, M. Leo, Tommaso Martiriggiano, T. D’orazio","doi":"10.1109/AVSS.2006.18","DOIUrl":"https://doi.org/10.1109/AVSS.2006.18","url":null,"abstract":"In this paper, a new method for a robust and efficient analysis of video sequences is presented; it allows the extraction of foreground objects and the classification of static foreground regions as abandoned or removed objects (ghosts). As a first step, the moving regions in the scene are detected by subtracting to the current frame a background model continuously adapted. Then, a shadow removing algorithm is used to extract the real shape of detected objects. Finally, moving objects are classified as abandoned or removed by matching the boundaries of static foreground regions. The method was successfully tested on both real image sequences acquired in our laboratory and some sequences from the PETS 2006 Datasets.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126456832","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: 47
Enhanced Kernel-Based Tracking for Monochromatic and Thermographic Video 单色和热成像视频的增强核跟踪
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.47
Q. A. Nguyen, A. Robles-Kelly, Chunhua Shen
{"title":"Enhanced Kernel-Based Tracking for Monochromatic and Thermographic Video","authors":"Q. A. Nguyen, A. Robles-Kelly, Chunhua Shen","doi":"10.1109/AVSS.2006.47","DOIUrl":"https://doi.org/10.1109/AVSS.2006.47","url":null,"abstract":"In this paper, we present an enhanced kernel-based tracker for monochromatic and thermographic video. The technique presented here employs the image intensity and the Local Binary Pattern (LBP) to construct a two dimensional histogram representative of the grayscale values and the texture of the target under study. With the histogram at hand, we proceed to compute its power density function. The new location of the object is then determined making use of a mean-shift optimisation approach. We illustrate the performance of our method in both, thermographic and monochromatic footages and compare our results to an alternative.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125092828","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: 12
A Compact Architecture for Wireless Video Surveillance over CDMA Network 基于CDMA网络的无线视频监控结构研究
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.4
Hang Zhou, D. Suter
{"title":"A Compact Architecture for Wireless Video Surveillance over CDMA Network","authors":"Hang Zhou, D. Suter","doi":"10.1109/AVSS.2006.4","DOIUrl":"https://doi.org/10.1109/AVSS.2006.4","url":null,"abstract":"Wireless video surveillance over CDMA network enables transfer of high quality live video via public wireless broadband, which is accessible anywhere with CDMA mobile phone network coverage. Real time video can be received on an internet connected PC, laptop or even mobile phone. This makes possible surveillance from moving vehicles, or quick deployment in almost unrestricted locations. While many general purpose solutions exist for sending video over CDMA, they have not taken into consideration certain specific features of the network nor the requirements of the related applications. This paper presents a new architecture for video transmission over CDMA with simple hardware complexity, high reliability and rich functions. The compact and flexible system has been under trial in China, Australia, Singapore, Italy, Egypt and Brazil, amongst others.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127632210","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
Real-Time Detection of Camera Tampering 实时检测摄像头篡改
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.94
E. Ribnick, S. Atev, O. Masoud, N. Papanikolopoulos, R. Voyles
{"title":"Real-Time Detection of Camera Tampering","authors":"E. Ribnick, S. Atev, O. Masoud, N. Papanikolopoulos, R. Voyles","doi":"10.1109/AVSS.2006.94","DOIUrl":"https://doi.org/10.1109/AVSS.2006.94","url":null,"abstract":"This paper presents a novel technique for camera tampering detection. It is implemented in real-time and was developed for use in surveillance and security applications. This method identifies camera tampering by detecting large differences between older frames of video and more recent frames. A buffer of incoming video frames is kept and three different measures of image dissimilarity are used to compare the frames. After normalization, a set of conditions is tested to decide if camera tampering has occurred. The effects of adjusting the internal parameters of the algorithm are examined. The performance of this method is shown to be extremely favorable in real-world settings.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"44 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133334933","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: 59
Geometry of a Non-Overlapping Multi-Camera Network 非重叠多摄像机网络的几何特性
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.53
Imran N. Junejo, Xiaochun Cao, H. Foroosh
{"title":"Geometry of a Non-Overlapping Multi-Camera Network","authors":"Imran N. Junejo, Xiaochun Cao, H. Foroosh","doi":"10.1109/AVSS.2006.53","DOIUrl":"https://doi.org/10.1109/AVSS.2006.53","url":null,"abstract":"Moving beyond single or stationary camera surveillance systems, we employ an automatically configurable network of non-overlapping cameras. These cameras need not have an overlapping Field of View (FoV) and should be able to move freely in space. In this paper, a practical framework is proposed that determines the geometry of such a dynamic camera network. Assuming each camera in the network is calibrated, it is shown that only one automatically computed vanishing point and a line lying on any plane orthogonal to the vertical direction is sufficient to infer the dynamic network configuration. Our method generalizes previous work which considers restricted camera motions. Using minimal assumptions, we are able to successfully demonstrate promising results on synthetic as well as on real data.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122919457","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
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