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

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3-D Virtual Environments on Mobile Devices for Remote Surveillance 移动设备上用于远程监控的三维虚拟环境
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.2
R. Vezzani, R. Cucchiara, A. Malizia, L. Cinque
{"title":"3-D Virtual Environments on Mobile Devices for Remote Surveillance","authors":"R. Vezzani, R. Cucchiara, A. Malizia, L. Cinque","doi":"10.1109/AVSS.2006.2","DOIUrl":"https://doi.org/10.1109/AVSS.2006.2","url":null,"abstract":"In this paper we present a distributed videosurveillance framework. Our end is the remote monitoring of the behavior of people moving in a scene exploiting a virtual reconstruction on low capabilities devices, like PDAs and cell phones. The main novelty of this system is the effective integration of the computer vision and computer graphics modules. The first, using a probabilistic frameworks, can detect the position, the trajectory and the posture of peoples moving in the scene. The second exploits the new possibility of both standard 3D graphics libraries on mobile (namely JSR184 and M3G graphic format) and new PDAs processing capability in order to reconstruct the remote surveillance data in real-time.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"100 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":"126319737","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: 1
On Person Authentication by Fusing Visual and Thermal Face Biometrics 融合视觉和热人脸生物识别技术的身份认证研究
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.86
Ognjen Arandjelovic, R. Hammoud, R. Cipolla
{"title":"On Person Authentication by Fusing Visual and Thermal Face Biometrics","authors":"Ognjen Arandjelovic, R. Hammoud, R. Cipolla","doi":"10.1109/AVSS.2006.86","DOIUrl":"https://doi.org/10.1109/AVSS.2006.86","url":null,"abstract":"Recognition algorithms that use data obtained by imaging faces in the thermal spectrum are promising in achieving invariance to extreme illumination changes that are often present in practice. In this paper we analyze the performance of a recently proposed face recognition algorithm that combines visual and thermal modalities by decision level fusion. We examine (i) the effects of the proposed data preprocessing in each domain, (ii) the contribution to improved recognition of different types of features, (iii) the importance of prescription glasses detection, in the context of both 1-to-N and 1-to-1 matching (recognition vs. verification performance). Finally, we discuss the significance of our results and, in particular, identify a number of limitations of the current state-of-the-art and propose promising directions for future research.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"31 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":"114398742","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: 39
A Study on Image Enhancement Techniques for Fingerprint Identification 指纹识别中的图像增强技术研究
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.14
Anto Paul, R. Lourde
{"title":"A Study on Image Enhancement Techniques for Fingerprint Identification","authors":"Anto Paul, R. Lourde","doi":"10.1109/AVSS.2006.14","DOIUrl":"https://doi.org/10.1109/AVSS.2006.14","url":null,"abstract":"The aim of this paper is to propose a new method in fingerprint enhancement with application of wavelet transform which is more efficient than existing methods. At present the methods that are in use are the ones involving the use of Gabor filtering and Fourier filtering. But the accuracy of these techniques is far from satisfactory. A new technique is being proposed that incorporates wavelet transform and Gabor filtering. The performance of this technique is being discussed in the paper.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"37 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":"134418248","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: 19
Real-Time Video Segmentation with VGA Resolution and Memory Bandwidth Reduction 实时视频分割与VGA分辨率和内存带宽减少
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.95
Hongtu Jiang, V. Öwall, H. Ardö
{"title":"Real-Time Video Segmentation with VGA Resolution and Memory Bandwidth Reduction","authors":"Hongtu Jiang, V. Öwall, H. Ardö","doi":"10.1109/AVSS.2006.95","DOIUrl":"https://doi.org/10.1109/AVSS.2006.95","url":null,"abstract":"This paper presents the implementation of a video segmentation unit used for embedded automated video surveillance systems. Various aspects of the underlying segmentation algorithm are explored and modifications are made with potential improvements of segmentation results and hardware efficiency. In addition, to achieve real-time performance with high resolution video streams, a dedicated hardware architecture with streamlined dataflow and memory access reduction schemes are developed. The whole system is implemented on a Xilinx FPGA platform, capable of real-time segmentation with VGA resolution at 25 frames per second. Substantial memory bandwidth reduction of more than 70% is achieved by utilizing pixel locality as well as wordlenghth reduction. The hardware platform is intended as a real-time testbench for observations of long term effects with different parameter settings, which is hard to achieve on a PC platform.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"13 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":"125300434","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
Motion Trajectory Classification for Visual Surveillance and Tracking 视觉监视与跟踪的运动轨迹分类
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.77
S. Dockstader
{"title":"Motion Trajectory Classification for Visual Surveillance and Tracking","authors":"S. Dockstader","doi":"10.1109/AVSS.2006.77","DOIUrl":"https://doi.org/10.1109/AVSS.2006.77","url":null,"abstract":"In this paper we present a video surveillance system for automated border and checkpoint analysis. The described system employs automated feature extraction and tracking to ascertain vehicle size, speed, and response to an interrogating vibration for vehicle bounce signature analysis. To increase the overall robustness of the surveillance system, we introduce a novel approach to invalid feature filtering. In particular, we use a hidden Markov model trained to simultaneously recognize specific coarse motion trajectories and tracking failures. The proposed recognition and filtering scheme effectively identifies erroneously tracked features and removes them prior to any subsequent motion analysis tasks. The result is a significant increase in classification and recognition accuracy. We demonstrate the efficacy of the suggested technique on a variety of video surveillance sequences.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"35 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":"127726360","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
Kernel Hetero-associative Memory for Robust Face Recognition 鲁棒人脸识别的核异联想记忆
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.68
Bai-ling Zhang
{"title":"Kernel Hetero-associative Memory for Robust Face Recognition","authors":"Bai-ling Zhang","doi":"10.1109/AVSS.2006.68","DOIUrl":"https://doi.org/10.1109/AVSS.2006.68","url":null,"abstract":"Associative memory models have been studied as efficient paradigm for visual information processing. In this paper we investigate a new hetero-associative memory (HAM) model based on the Kernel Partial Least Square (KPLS) regression recently proposed in the literature. Steming from the Partial Least Square (PLS) regression, a class of techniques for modeling relations between blocks of observed variables by means of latent variables, kernelized PLS methods have proved to be efficient in treating nonlinear data. By establishing the relations between sets of observed variables, KPLS can provide a general purpose HAM model, which construct nonlinear regression models in possibly high-dimensional feature spaces and uses a few latent factors to account for most of the variations in the response. For face recognition problem, we apply the HAM model to efficiently characterize each subject by relating some possible variations of a face image to a given face, using a modular strudcture by assigning an independent model to each subject. Several benchmark face databases have been used to test the performance.","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":"127743524","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
An Efficient Video Enhancement Method Using LA*B* Analysis 一种基于LA*B*分析的高效视频增强方法
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.20
G. Mittal, Sushrutha Locharam, S. Sasi, G. R. Shaffer, Ajith K. Kumar
{"title":"An Efficient Video Enhancement Method Using LA*B* Analysis","authors":"G. Mittal, Sushrutha Locharam, S. Sasi, G. R. Shaffer, Ajith K. Kumar","doi":"10.1109/AVSS.2006.20","DOIUrl":"https://doi.org/10.1109/AVSS.2006.20","url":null,"abstract":"In this paper, an efficient technique is proposed for real-time enhancement of video containing inconsistent and complex conditions like nonuniform and insufficient lighting. Beyond providing digital tools for video enhancement, this method provides a better approach to enhance a video in low lighting conditions without any loss of color information. This approach is based on histogram manipulations on La*b* color model of the video frame. This algorithm provides an effective way for video enhancement with simple computational procedures, which makes real-time enhancement for homeland security application successfully realized. Simulation is done on videos taken under bad lighting conditions and results are presented.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"51 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":"116604358","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: 8
Effect of Finite Sample Size in Content-Based Image Retrieval 有限样本容量对基于内容的图像检索的影响
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.46
G. Das, S. Ray
{"title":"Effect of Finite Sample Size in Content-Based Image Retrieval","authors":"G. Das, S. Ray","doi":"10.1109/AVSS.2006.46","DOIUrl":"https://doi.org/10.1109/AVSS.2006.46","url":null,"abstract":"Finite sample size has always been a problem in determining the retrieval accuracy of a Content-Based Image Retrieval (CBIR) system. Though a good amount of research has been done in the statistical pattern recognition field, no such effort is shown in relation to CBIR. In this paper, we considered image retrieval as a dichotomous classification problem and studied the effect of sample size on the retrieval accuracy. We reported experimental results and analysis with two different image databases of size 2000 and 500, both having 10 semantic categories. For both data sets, we showed the variation of precision with sample size. We also studied the effect of sample size on retrieval accuracy as Relevance Feedback (RF) is applied. For both data sets, the nett improvement in precision with RF increases with sample size.","PeriodicalId":289876,"journal":{"name":"2006 IEEE International Conference on Video and Signal Based Surveillance","volume":"59 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":"127576324","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
High-Quality Real Time Motion Detection Using PTZ Cameras 使用PTZ相机的高质量实时运动检测
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.57
A. Bevilacqua, Pietro Azzari
{"title":"High-Quality Real Time Motion Detection Using PTZ Cameras","authors":"A. Bevilacqua, Pietro Azzari","doi":"10.1109/AVSS.2006.57","DOIUrl":"https://doi.org/10.1109/AVSS.2006.57","url":null,"abstract":"The approaches based on background difference are the most used with fixed cameras to perform motion detection, because of the high quality of the segmentation achieved. However, real time requirements prevent most of the algorithms proposed in literature to exploit the background difference with Pan-Tilt-Zoom (PTZ) cameras in real world applications. Nevertheless, using color information to detect motion yields a sensible improvement in terms of accuracy of segmented masks, by helping reducing camouflage and detecting shadows. To our knowledge, the algorithm we have conceived is the first to exploit color information and perform real time alignment and background difference based on background mosaicing, with PTZ cameras. In addition, no prior information regarding scene or camera parameters have been used for either spatial or tonal alignment. Accurate experiments performed on indoor and outdoor sequences allow to assess both quality and performance of the method we devised.","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":"121921415","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: 52
Independent Moving Object Detection Using a Colour Background Model 使用彩色背景模型的独立运动目标检测
2006 IEEE International Conference on Video and Signal Based Surveillance Pub Date : 2006-11-22 DOI: 10.1109/AVSS.2006.67
F. Campbell-West, P. Miller, Hongbin Wang
{"title":"Independent Moving Object Detection Using a Colour Background Model","authors":"F. Campbell-West, P. Miller, Hongbin Wang","doi":"10.1109/AVSS.2006.67","DOIUrl":"https://doi.org/10.1109/AVSS.2006.67","url":null,"abstract":"An independent moving objection detection system is described which uses a colour background model for a nonstationary sensor. Over time the RGB distribution of a static point in a scene, observed from a static or moving camera, is cylindrical rather than spherical and is modelled as such. The background model is recursively updated over time and is robustly aligned to the most recent frame. Discrepancies between the current observed frame and the background model are considered foreground events and are determined using a classification framework which combines per-pixel colour and brightness differences. In principle the colour (RGB) images provide greater discriminative power than greyscale (brightness). However for several sequences tested, which are of road scenes from an airborne sensor, it was found that the colour information did not improve the classification of foreground pixels significantly.","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":"131798324","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
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