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

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A Multi-Class Tracker Using a Scalable Condensation Filter 使用可伸缩冷凝过滤器的多类跟踪器
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.7
S. Denman, V. Chandran, S. Sridharan, C. Fookes
{"title":"A Multi-Class Tracker Using a Scalable Condensation Filter","authors":"S. Denman, V. Chandran, S. Sridharan, C. Fookes","doi":"10.1109/AVSS.2006.7","DOIUrl":"https://doi.org/10.1109/AVSS.2006.7","url":null,"abstract":"Tracking systems are typically targeted towards tracking a single class of object. In many real world situations, and in the ETISEO evaluation, it is advantageous to be able to track multiple classes of objects. In this paper we describe the adaptation of a single class tracking system to a multi-class tracking system, and describe a modified version of the condensation filter that can be used to track all objects, of all classes. We show that by using simple targeted detectors, we can achieve accurate tracking and can accurately distinguish between classes.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"24 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":"129362139","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: 4
Combining Shape-from-Motion Output with Partial Metadata 结合运动形状输出和部分元数据
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.36
R. Whatmough
{"title":"Combining Shape-from-Motion Output with Partial Metadata","authors":"R. Whatmough","doi":"10.1109/AVSS.2006.36","DOIUrl":"https://doi.org/10.1109/AVSS.2006.36","url":null,"abstract":"When the positions of the camera are not given, shape-from-motion methods can use target feature positions identified in a sequence of images to extract the three-dimensional positions of the features and the orientations of the camera relative to the target. These methods can be applied to video sequences taken from an aircraft, but do not reveal the overall size, orientation or geographic location of the target. If the camera is combined with a system that records its location, orientation and focal length, at least approximately for a few of the images, the target size, orientation and location can be estimated In certain cases, some of this information can be estimated from the image sequence itself. This paper considers the theory and practice of combining the shape extraction with the available camera information.","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":"127356495","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
CBIR Approach to Building Image Retrieval Based on Linear Edge Distribution 基于线性边缘分布的CBIR建筑图像检索方法
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.31
Xiang Yuan, Chang-Tsun Li
{"title":"CBIR Approach to Building Image Retrieval Based on Linear Edge Distribution","authors":"Xiang Yuan, Chang-Tsun Li","doi":"10.1109/AVSS.2006.31","DOIUrl":"https://doi.org/10.1109/AVSS.2006.31","url":null,"abstract":"In this paper, we propose a CBIR approach to retrieve building images. First, we use the Canny edge detector to extract edge information from the images. Secondly, the Hough transform is applied to the edge map in order to reveal the linear edge distribution in the Hough transform domain. Thirdly, by using a Band-wise matching (BWM) algorithm, we partition the Hough transform domain into a number of bands and calculate the centroid of the Hough peaks in each band. By carrying out the same aforementioned procedures on a query image and the images in the database, we measure the similarity between the centroids of the query image and the images in the database. Finally, based on the similarity measures, the CBIR system ranks the images in the database and retrieves a specified number of images with the highest rankings.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"63 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":"128795436","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: 5
Learning a New Statistical Shape Prior Model for Object Detection by Geodesic Active Contours 学习一种新的基于测地线活动轮廓的统计形状先验模型
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.70
W. Fang, K. Chan
{"title":"Learning a New Statistical Shape Prior Model for Object Detection by Geodesic Active Contours","authors":"W. Fang, K. Chan","doi":"10.1109/AVSS.2006.70","DOIUrl":"https://doi.org/10.1109/AVSS.2006.70","url":null,"abstract":"A new statistical shape prior model is proposed in this paper which is incorporated into geodesic active contours for robust object detection. The object shapes that undergo nonlinear deformable changes are assumed to lie in a low dimensional feature subspace and form clusters after a nonlinear mapping. They are approximated by a probabilistic density model to explore the structure of data distribution. The obtained probability is treated as a shape energy term and is incorporated into geodesic active contour equation to constrain the further curve evolution process. This shape prior model is based on a more sophisticated statistical learning of the training data distribution and thus is more robust in presence of occlusions and cluttered background. Experiments demonstrate its promising detection performance for the intended tasks.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"1 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":"129187647","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
Car Plate Detection Using Cascaded Tree-Style Learner Based on Hybrid Object Features 基于混合目标特征的级联树型学习器车牌检测
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.30
Qiang Wu, Huaifeng Zhang, W. Jia, Xiangjian He, Jie Yang, T. Hintz
{"title":"Car Plate Detection Using Cascaded Tree-Style Learner Based on Hybrid Object Features","authors":"Qiang Wu, Huaifeng Zhang, W. Jia, Xiangjian He, Jie Yang, T. Hintz","doi":"10.1109/AVSS.2006.30","DOIUrl":"https://doi.org/10.1109/AVSS.2006.30","url":null,"abstract":"Car plate detection is a key component in automatic license plate recognition system. This paper adopts an enhanced cascaded tree style learner framework for car plate detection using the hybrid object features including the simple statistical features and Harr-like features. The statistical features are useful for simplifying the process on cascade classifier. The cascaded tree-style detector design will further reduce the false alarm and the false dismissal while retaining a high detection ratio. The experimental results obtained by the proposed algorithm exhibit the encouraging performance.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"148 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":"114635547","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
Discovering the Local Co-occurring Patterns in Visual Categorization 发现视觉分类中的局部共发生模式
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.41
Hongbin Wang, P. Miller, P. Culverhouse
{"title":"Discovering the Local Co-occurring Patterns in Visual Categorization","authors":"Hongbin Wang, P. Miller, P. Culverhouse","doi":"10.1109/AVSS.2006.41","DOIUrl":"https://doi.org/10.1109/AVSS.2006.41","url":null,"abstract":"We present a novel visual representation, called local co-occurring patterns (LCPs), which consists of characteristic local features and the statistical co-occurance relations between them. The LCPs can be discovered using an associate rule mining algorithm. Experiments show that LCPs widely exist in a large image corpus, and are more discriminant than individual local features in visual categorization tasks such as subcategory and face recognition. Furthermore, state-of-the-art categorization performance was achieved on two test data-sets.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"9 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":"114895673","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
DNA Microarray Image Enhancement Using Conditional Sub-Block Bi-Histogram Equalization 使用条件子块双直方图均衡化的DNA微阵列图像增强
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.43
Nader Saffarian, J. Zou
{"title":"DNA Microarray Image Enhancement Using Conditional Sub-Block Bi-Histogram Equalization","authors":"Nader Saffarian, J. Zou","doi":"10.1109/AVSS.2006.43","DOIUrl":"https://doi.org/10.1109/AVSS.2006.43","url":null,"abstract":"In this paper, a new image enhancement approach is proposed, which has the ability to improve the gridding results in DNA microarray analysis. The proposed approach is implemented as a conditional sub-block bi-histogram equalization (CSBE). This is accomplished by first, decomposing an input image into a number of m x n sub-blocks. Second, the threshold of each sub-block is determined independently. Third, the sub-block is divided into two sub-images based on the threshold. Fourth, only pixels having value greater than the threshold are histogram equalized, and the two sub-images are then recombined. The proposed method is tested on various DNA microarray images, giving excellent results, compared to existing methods.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"7 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":"121148152","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
Dynamic Scene Reconstruction for Efficient Remote Surveillance 高效远程监控的动态场景重建
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.45
A. Calbi, C. Regazzoni, L. Marcenaro
{"title":"Dynamic Scene Reconstruction for Efficient Remote Surveillance","authors":"A. Calbi, C. Regazzoni, L. Marcenaro","doi":"10.1109/AVSS.2006.45","DOIUrl":"https://doi.org/10.1109/AVSS.2006.45","url":null,"abstract":"In this paper a system is presented able to reproduce the actions of multiple moving objects into a 3D model. A multi-camera surveillance system is used for automatically detect, track and classify the objects. Data fusion from multiple sensors allows to get a more precise estimation of the position of detected moving objects and to solve occlusions problem. These data are then used to automatically place and animate objects avatars in a 3D virtual model of the scene, thus allowing a human operator to remotely visualize the dynamic 3D reconstruction by selecting a arbitrary point of view.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"7 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":"115166861","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: 7
Multi-view Intelligent Vehicle Surveillance System 多视角智能车辆监控系统
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.78
S. Denman, C. Fookes, Jamie Cook, Chris Davoren, Anthony Mamic, G. Farquharson, Daniel Chen, Brenden Chen, S. Sridharan
{"title":"Multi-view Intelligent Vehicle Surveillance System","authors":"S. Denman, C. Fookes, Jamie Cook, Chris Davoren, Anthony Mamic, G. Farquharson, Daniel Chen, Brenden Chen, S. Sridharan","doi":"10.1109/AVSS.2006.78","DOIUrl":"https://doi.org/10.1109/AVSS.2006.78","url":null,"abstract":"This paper presents a multi-view intelligent surveillance system used for the automatic tracking and monitoring of vehicles in a short-term parking lane. The system has the ability to track multiple vehicles in real-time across four cameras monitoring the area using a combination of both motion detection and optical flow modules. Automated alerts of events such as parking time violations, breaching of restricted areas or improper directional flow of traffic can be generated and communicated to attending security personnel. Results are shown using surveillance data captured from a real multi-camera network to illustrate the robust and real-time performance of the system.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"25 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":"121813452","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
Omni-Directional Camera Networks and Data Fusion for Vehicle Tracking in an Indoor Parking Lot 面向室内停车场车辆跟踪的全向摄像机网络与数据融合
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.84
Jung-Ming Wang, Ching-Ting Tsai, Shen Cherng, Sei-Wang Chen
{"title":"Omni-Directional Camera Networks and Data Fusion for Vehicle Tracking in an Indoor Parking Lot","authors":"Jung-Ming Wang, Ching-Ting Tsai, Shen Cherng, Sei-Wang Chen","doi":"10.1109/AVSS.2006.84","DOIUrl":"https://doi.org/10.1109/AVSS.2006.84","url":null,"abstract":"A fixed single camera is not sufficient for monitoring a wide area. More cameras can be used, but a problem with integrating all of them will arise. In this paper, a monitoring system to detect and track moving objects in an indoor environment using multiple omni-directional cameras is proposed. Objects captured from different cameras can be integrated automatically, and we can add more cameras to enlarge the monitoring range without changing the system architecture. Such a system is currently being applied to a model of a parking lot for detecting the paths of vehicles.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"1 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":"125790406","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: 4
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