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18th International Conference on Pattern Recognition (ICPR'06)最新文献

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Local Visual Primitives (LVP) for Face Modelling and Recognition 局部视觉原语(LVP)用于人脸建模和识别
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.773
Xin Meng, S. Shan, Xilin Chen, Wen Gao
{"title":"Local Visual Primitives (LVP) for Face Modelling and Recognition","authors":"Xin Meng, S. Shan, Xilin Chen, Wen Gao","doi":"10.1109/ICPR.2006.773","DOIUrl":"https://doi.org/10.1109/ICPR.2006.773","url":null,"abstract":"This paper proposes a novel simple yet effective generative model based on local visual primitives (LVP) for face modeling and classification. The LVPs, as the pattern of local face region, are learnt by clustering a great number of local patches. Visually, these LVPs correspond to intuitive low-level micro visual structures very well, and they are expected to constitute those high-level semantic features, such as eyes, nose and mouth. We show that, though face appearances vary dramatically, these LVPs are very effective for face image reconstruction. For face recognition, block-based histograms of the LVPs indexes are extracted as the face representation to compare for classification. Primary experiments on FERET face database have shown that the LVP method can achieve encouraging recognition rate","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129343239","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: 33
ViSE: Visual Search Engine Using Multiple Networked Cameras ViSE:使用多个网络摄像机的视觉搜索引擎
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.1176
U. Park, Anil K. Jain, I. Kitahara, K. Kogure, N. Hagita
{"title":"ViSE: Visual Search Engine Using Multiple Networked Cameras","authors":"U. Park, Anil K. Jain, I. Kitahara, K. Kogure, N. Hagita","doi":"10.1109/ICPR.2006.1176","DOIUrl":"https://doi.org/10.1109/ICPR.2006.1176","url":null,"abstract":"We propose a visual search engine (ViSE) as a semi-automatic component in a surveillance system using networked cameras. The ViSE aims to assist the monitoring operation of huge amounts of captured video streams, which tracks and finds people in the video based on their primitive features with the interaction of a human operator. We address the issues of object detection and tracking, shadow suppression and color-based recognition for the proposed system. The experimental results on a set of video data with ten subjects showed that ViSE retrieves correct candidates with 83% recall at 83% precision","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123476346","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: 130
Age simulation for face recognition 年龄模拟人脸识别
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.230
Junyan Wang, Y. Shang, G. Su, Xinggang Lin
{"title":"Age simulation for face recognition","authors":"Junyan Wang, Y. Shang, G. Su, Xinggang Lin","doi":"10.1109/ICPR.2006.230","DOIUrl":"https://doi.org/10.1109/ICPR.2006.230","url":null,"abstract":"In this paper, an automatic age simulation method used for robust face recognition is proposed. We first use a shape and texture vectors to represent a facial image by projecting it in the eigenspace of shape or texture. Then we use age function combined with aging way classification to estimate age. And we use estimated age, typical vector creating function and the feature vector of the original test image to generate the synthesized feature vectors at target age. At last we reconstruct the shape and texture in eigenspaces and combine them to synthesize facial image at target age. Experiments show that the proposed method can effectively \"change\" the age of face images, and help to get face recognition result robust to age variation","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123536032","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: 89
Robust Eye Detection under Active Infrared Illumination 主动红外照明下的鲁棒眼检测
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.1004
Shuyan Zhao, R. Grigat
{"title":"Robust Eye Detection under Active Infrared Illumination","authors":"Shuyan Zhao, R. Grigat","doi":"10.1109/ICPR.2006.1004","DOIUrl":"https://doi.org/10.1109/ICPR.2006.1004","url":null,"abstract":"Eye detection is very important for automatic face recognition and gaze tracking. In this paper we propose an algorithm for eye detection under active infrared (IR) illumination. A simple hardware enables us to make use of a physiological property of the eyes. A new thresholding method is introduced in order to effectively search the regions of interest (ROI). An appearance model is then used to verify the pupil candidates. However, the existence of eyeglasses has a negative effect on selection of candidates. Regarding this the generalized symmetry transform (GST) is exploited. By using a simplified distance weight, we reduce the computational cost of the original transform. Experimental results demonstrate the effectiveness of the proposed eye detection method","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123647466","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: 46
Ball Hit Detection in Table Tennis Games Based on Audio Analysis 基于音频分析的乒乓球比赛击球检测
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.314
Bin Zhang, W. Dou, Liming Chen
{"title":"Ball Hit Detection in Table Tennis Games Based on Audio Analysis","authors":"Bin Zhang, W. Dou, Liming Chen","doi":"10.1109/ICPR.2006.314","DOIUrl":"https://doi.org/10.1109/ICPR.2006.314","url":null,"abstract":"As bearer of high level semantics, audio signal is being more and more used in content-based multimedia retrieval. In this paper, we investigate the ball hit detection for sports games and propose a novel approach to detect ball hits. By employing energy peak detection (EPD) and Mel frequency cepstral coefficient-based (MFCC-based) refinement (MBR), high precision (91%) and adequate recall (73%) of ball hit detection are achieved with a low computational complexity and an easy training process. The proposed algorithm can be applied in audio content-based highlight detection systems and provide valuable information for semantical understanding of sports games","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121389338","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
Boosted Band Ratio Feature Selection for Hyperspectral Image Classification 用于高光谱图像分类的增强带比特征选择
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.334
Zhouyu Fu, T. Caelli, Nianjun Liu, A. Robles-Kelly
{"title":"Boosted Band Ratio Feature Selection for Hyperspectral Image Classification","authors":"Zhouyu Fu, T. Caelli, Nianjun Liu, A. Robles-Kelly","doi":"10.1109/ICPR.2006.334","DOIUrl":"https://doi.org/10.1109/ICPR.2006.334","url":null,"abstract":"Band ratios have many useful applications in hyperspectral image analysis. While optimal ratios have been chosen empirically in previous research, we propose a principled algorithm for the automatic selection of ratios directly from data. First, a robust method is used to estimate the Kullback-Leibler divergence (KLD) between different sample distributions and evaluate the optimality of individual ratio features. Then, the boosting framework is adopted to select multiple ratio features iteratively. Multiclass classification is handled by using a pairwise classification framework. The algorithm can also be applied to the selection of discriminant bands. Experimental results on both simple material identification and complex land cover classification demonstrate the potential of this ratio selection algorithm","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114308418","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: 17
Robust Detection of Region-Duplication Forgery in Digital Image 数字图像区域重复伪造的鲁棒检测
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.1003
Weiqi Luo, Jiwu Huang, G. Qiu
{"title":"Robust Detection of Region-Duplication Forgery in Digital Image","authors":"Weiqi Luo, Jiwu Huang, G. Qiu","doi":"10.1109/ICPR.2006.1003","DOIUrl":"https://doi.org/10.1109/ICPR.2006.1003","url":null,"abstract":"Region duplication forgery, in which a part of a digital image is copied and then pasted to another portion of the same image in order to conceal an important object in the scene, is one of the common image forgery techniques. In this paper, we describe an efficient and robust algorithm for detecting and localizing this type of malicious tampering. We present experimental results which show that our method is robust and can successfully detect this type of tampering for images that have been subjected to various forms of post region duplication image processing, including blurring, noise contamination, severe lossy compression, and a mixture of these processing operations","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114531406","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: 315
Image Analysis of Renal DCE MRI for the Detection of Acute Renal Rejection 肾DCE MRI检测急性肾排斥反应的影像分析
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.679
A. El-Baz, A. Farag, Rachid Fahmi, S. E. Yüksel, M. El-Ghar, T. Eldiasty
{"title":"Image Analysis of Renal DCE MRI for the Detection of Acute Renal Rejection","authors":"A. El-Baz, A. Farag, Rachid Fahmi, S. E. Yüksel, M. El-Ghar, T. Eldiasty","doi":"10.1109/ICPR.2006.679","DOIUrl":"https://doi.org/10.1109/ICPR.2006.679","url":null,"abstract":"Acute rejection is the most common reason of graft failure after kidney transplantation, and early detection is crucial to survive the transplanted kidney function. In this paper we introduce a new approach for the automatic classification of normal and acute rejection transplants from dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). The proposed algorithm consists of three main steps; the first step isolates the kidney from the surrounding anatomical structures. In the second step, a novel nonrigid-registration algorithm is employed to account for the motion of the kidney due to patient breathing, and finally, the perfusion curves that show the transportation of the contrast agent into the tissue are obtained from the cortex and used in the classification of normal and acute rejection transplants. Applications of the proposed approach yield promising results","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121501906","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: 31
High Accuracy Handwritten Chinese Character Recognition Using Quadratic Classifiers with Discriminative Feature Extraction 基于判别特征提取的二次分类器的高精度手写体汉字识别
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.624
Cheng-Lin Liu
{"title":"High Accuracy Handwritten Chinese Character Recognition Using Quadratic Classifiers with Discriminative Feature Extraction","authors":"Cheng-Lin Liu","doi":"10.1109/ICPR.2006.624","DOIUrl":"https://doi.org/10.1109/ICPR.2006.624","url":null,"abstract":"We aim to improve the accuracy of handwritten Chinese character recognition using two advanced techniques: discriminative feature extraction (DFE) and discriminative learning quadratic discriminant function (DLQDF). Both methods are based on the minimum classification error (MCE) training method of Juang et al. (1992), and we propose to accelerate the training process on large category set using hierarchical classification. Our experimental results on two large databases show that while the DFE improves the accuracy significantly, the DLQDF improves only slightly. Compared to the modified quadratic discriminant function (MQDF) with Fisher discriminant analysis, the error rates on two test sets were reduced by factors of 29.9% and 20.7%, respectively","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121596205","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
A Maximum A Posteriori Probability Viterbi Data Association Algorithm for Ball Tracking in Sports Video 体育视频球跟踪的最大后验概率Viterbi数据关联算法
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.95
F. Yan, W. Christmas, J. Kittler
{"title":"A Maximum A Posteriori Probability Viterbi Data Association Algorithm for Ball Tracking in Sports Video","authors":"F. Yan, W. Christmas, J. Kittler","doi":"10.1109/ICPR.2006.95","DOIUrl":"https://doi.org/10.1109/ICPR.2006.95","url":null,"abstract":"In this paper, we derive a data association algorithm for object tracking in a maximum a posteriori framework: the output of the algorithm is the sequence of measurement-to-target associations with maximum a posteriori probability. We model the object motion as a Markov process, and solve this otherwise combinatorially complex problem efficiently by applying the Viterbi algorithm. A method for combining forward and backward tracking results is also developed, to recover from tracking errors caused by abrupt motion changes of the object. The proposed algorithm is applied to broadcast tennis video to track a tennis ball. Experiments show that its performance is comparable to that of a computationally more expensive particle-filter-based algorithm","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121658179","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: 17
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