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2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System最新文献

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Joint Compression and Classification for Textures in the Wavelet and Ridgelet Domain 小波和脊波域纹理的联合压缩与分类
2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System Pub Date : 2007-12-16 DOI: 10.1109/SITIS.2007.57
M. Joshi, R. Manthalkar, Y. Joshi
{"title":"Joint Compression and Classification for Textures in the Wavelet and Ridgelet Domain","authors":"M. Joshi, R. Manthalkar, Y. Joshi","doi":"10.1109/SITIS.2007.57","DOIUrl":"https://doi.org/10.1109/SITIS.2007.57","url":null,"abstract":"Image Compression is a widely addressed research area. Many compression standards are in place. There are many methods for image classification. But the joint compression and classification is a new research area wherein the classification is attempted in the compressed domain. The joint compression and classification (JCC) is explored in wavelet domain by some researchers. But it is not yet explored in Ridgelet domain. This paper discusses the performance of JCC for Wavelet and Ridgelet domain for Texture images. The experimentation is done with objective analysis and subjective analysis. Objective analysis is performed using the Compression metrics-RMSE, PSNR and classification metric- CCR. Subjective analysis is performed using Human Visual Perception. It is found that the Ridgelet Transform gives less Mean Squared Error (MSE) and is better for Joint Compression and Classification of Texture images. Extensive experimentation has been carried out to arrive at the conclusion.","PeriodicalId":234433,"journal":{"name":"2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125758313","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
Wraplet: Wrapping Your Web Contents with a Lightweight Language 用一种轻量级语言包装你的网页内容
2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System Pub Date : 2007-12-16 DOI: 10.1109/SITIS.2007.135
Natsumi Sawa, Atsuyuki Morishima, S. Sugimoto, H. Kitagawa
{"title":"Wraplet: Wrapping Your Web Contents with a Lightweight Language","authors":"Natsumi Sawa, Atsuyuki Morishima, S. Sugimoto, H. Kitagawa","doi":"10.1109/SITIS.2007.135","DOIUrl":"https://doi.org/10.1109/SITIS.2007.135","url":null,"abstract":"Wrapping of Web sources is known to be one of the key tasks in information integration problems. This paper proposes Wraplet, a wrapping language for extracting structured data from Web contents written in HTML. Unlike existing solutions, Wraplet is designed as a lightweight language in which users can write scripts for wrapping easily with text editors. Its simple syntax and the library of useful patterns help the user write wrapping descriptions by hand. We explain the motivation of its development and the language design and then shows the result of a preliminary experiment about applicability of the language to real Web sources. We conducted a statistical analysis and obtained the result that the applicability of Wraplet is more than 90% at the 95% confidence level in the experimental setting.","PeriodicalId":234433,"journal":{"name":"2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121941659","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
A Simulated Annealing and 2DPCA Based Method for Face Recognition 基于模拟退火和2DPCA的人脸识别方法
2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System Pub Date : 2007-12-16 DOI: 10.1109/SITIS.2007.62
Zhijie Xu, Laisheng Wang, Liming Yang
{"title":"A Simulated Annealing and 2DPCA Based Method for Face Recognition","authors":"Zhijie Xu, Laisheng Wang, Liming Yang","doi":"10.1109/SITIS.2007.62","DOIUrl":"https://doi.org/10.1109/SITIS.2007.62","url":null,"abstract":"In this paper we address the problem of face recognition based on two-dimensional principal component analysis (2DPCA). The similarity measure plays an important role in pattern recognition. However, with reference to the 2DPCA based method for face recognition, studies on similarity measures are quite few. We propose a new method to identify the similarity measure by simulated annealing (SA), which is called SA similarity measure. Experimental results on two famous face databases show that the proposed method outperforms the state of the art methods in terms of recognition accuracy.","PeriodicalId":234433,"journal":{"name":"2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117009705","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
A Methodology for Low-Cost Image Annotation Based on Conceptual Modeling: A Biological Example 一种基于概念建模的低成本图像标注方法:一个生物学实例
2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System Pub Date : 2007-12-16 DOI: 10.1109/SITIS.2007.97
A. Costa, É. Leclercq, M. Savonnet, M. Terrasse
{"title":"A Methodology for Low-Cost Image Annotation Based on Conceptual Modeling: A Biological Example","authors":"A. Costa, É. Leclercq, M. Savonnet, M. Terrasse","doi":"10.1109/SITIS.2007.97","DOIUrl":"https://doi.org/10.1109/SITIS.2007.97","url":null,"abstract":"In the context of data-intensive biology applications the overall annotation costs are rather high since experts generally need to be involved. In some cases it is possible to automate the annotation process. In this paper we propose an approach that consists in building an image database application that enables domain technicians to make annotations without compromizing their semantical precision. Our proposal relies mainly on a domain ontology coupled with a conceptual data model.","PeriodicalId":234433,"journal":{"name":"2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129839069","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
Selection of Reliable Features Subsets for Appearance-Based Tracking 基于外观跟踪的可靠特征子集的选择
2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System Pub Date : 2007-12-16 DOI: 10.1109/SITIS.2007.83
Pascaline Parisot, B. Thiesse, V. Charvillat
{"title":"Selection of Reliable Features Subsets for Appearance-Based Tracking","authors":"Pascaline Parisot, B. Thiesse, V. Charvillat","doi":"10.1109/SITIS.2007.83","DOIUrl":"https://doi.org/10.1109/SITIS.2007.83","url":null,"abstract":"Efficient algorithms that track targets with a constant aspect (rigid objects, for example) are often based on appearance models. The simplest models linearly predict motion parameters from gray-scale variations measured at features. Choosing the features and training the predictor is done during a preliminary off-line stage. This paper presents several methods that improve the features selection process by filtering out some features from a given set. In particular, we are interested in the SVD-based subset selection procedure proposed by Golub and Van Loan. We show a significant improvement of tracking performance when our method filters Moravec, Harris, KLT or SUSAN features. We conclude that individually good selected features may not build a good subset and that a good spatial distribution of the features is paramount.","PeriodicalId":234433,"journal":{"name":"2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129516424","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: 6
Vision-Based 3D Articulated Pose Tracking Using Particle Filtering and Model Constraints 使用粒子滤波和模型约束的基于视觉的3D关节姿态跟踪
2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System Pub Date : 2007-12-16 DOI: 10.1109/SITIS.2007.35
Fawang Liu, Gangyi Ding, X. Deng, Yihua Xu
{"title":"Vision-Based 3D Articulated Pose Tracking Using Particle Filtering and Model Constraints","authors":"Fawang Liu, Gangyi Ding, X. Deng, Yihua Xu","doi":"10.1109/SITIS.2007.35","DOIUrl":"https://doi.org/10.1109/SITIS.2007.35","url":null,"abstract":"We describe a probabilistic approach for 3D upper body pose tracking by fusing depth, color and underlying body constraints. Existing tracking algorithms can be roughly divided into model-free and model-based methods. Probabilistic assembly of parts falls into model-free category. An important advantage of this technique is that pose can be estimated independently at each frame, allowing estimation for rapid movements, but most such approaches only get 2D tracking results. The use of an explicit model is the most widely investigated methodology, but often suffers from high computational costs. In this paper, we employ particle filtering to get candidate body parts with salient features, integrate probabilistic assembly of parts with model constraints to get the best pose configuration. Experimental results show that our approach can robustly track human motion even when hands move rapidly or self-occlusion exists, and can also automatically initialize and recover from tracking failure.","PeriodicalId":234433,"journal":{"name":"2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131581514","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
Three User Profile Similarity Calculation (UPSC) Methods and Their Evaluation 三种用户轮廓相似度计算方法及其评价
2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System Pub Date : 2007-12-16 DOI: 10.1109/SITIS.2007.132
H. Naderi, B. Rumpler
{"title":"Three User Profile Similarity Calculation (UPSC) Methods and Their Evaluation","authors":"H. Naderi, B. Rumpler","doi":"10.1109/SITIS.2007.132","DOIUrl":"https://doi.org/10.1109/SITIS.2007.132","url":null,"abstract":"Collaborative information retrieval (CIR) is a new technique for resolving the current problem of information retrieval systems. A CIR system registers the previous user interactions to response to the subsequent user queries more efficiently. However well-known problem of personalization in retrieval systems is more acute in CIR systems. The goals and the characteristics of two users may be different; so when they send the same query to a CIR system, they may be interested in two different lists of documents. To solve this problem, we have developed a personalized CIR system, called PERCIRS, based onthe user profiles' similarity to satisfy their queries.Thus selecting an efficient method to calculate the similarity between user profiles is a key factor for enhancing PERCIRSpsilas efficiency. In this paper, we propose three methods for user profile similarity calculation. Finally, we introduce a mechanism for evaluating these methods.","PeriodicalId":234433,"journal":{"name":"2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132518760","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
Texture or Color Analysis in Agronomic Images for Wheat Ear Counting 用于小麦穗计数的农艺图像的纹理或颜色分析
2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System Pub Date : 2007-12-16 DOI: 10.1109/SITIS.2007.80
F. Cointault, P. Gouton
{"title":"Texture or Color Analysis in Agronomic Images for Wheat Ear Counting","authors":"F. Cointault, P. Gouton","doi":"10.1109/SITIS.2007.80","DOIUrl":"https://doi.org/10.1109/SITIS.2007.80","url":null,"abstract":"In agronomy, image processing techniques are more and more used to detect crop, weeds, diseases ... We proposed to study the feasibility to use color and/or texture analysis to evaluate the number of wheat ears per m2 to simplify the manual countings currently done. In this paper we present firstly the use of color and texture image processing together to detect the ears, before to propose and compare different texture image segmentation techniques based on feature extraction by first and higher order statistical methods. The extracted features are used for unsupervised pixel classification to obtain the different classes in the image, before to use the k-means algorithm. Three methods have been tested with very heterogeneous results, except the run length technique for which the results are close to the manual countings (66% error). The hypothesis took into account for the textural analysis methods are currently modify to justify them more accurately, especially concerning the number of classes and the size of the analysis window.","PeriodicalId":234433,"journal":{"name":"2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121982518","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: 21
Topic Detection via Participation Using Markov Logic Network 基于马尔可夫逻辑网络的参与式主题检测
2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System Pub Date : 2007-12-16 DOI: 10.1109/SITIS.2007.55
V. Cheng, Chun-hung Li
{"title":"Topic Detection via Participation Using Markov Logic Network","authors":"V. Cheng, Chun-hung Li","doi":"10.1109/SITIS.2007.55","DOIUrl":"https://doi.org/10.1109/SITIS.2007.55","url":null,"abstract":"The advent of Web 2.0 enables the proliferation of online communities in which tremendous number of Internet users contribute and share enormous information. Proper exploitation of community structure help retrieving useful information and better understanding of their features. We employ Markov Logic Network to explore topic tracking by finding clusters, which represents latent topics, best fitting a set of rules. Rather than using contents in investigating discussions of a community, the user participation is used because it is believed that topics can be somehow reflected by the preferences of participation. User participation is also easier to process than text. The clustering results show this approach can reveal latent topics of a community effectively.","PeriodicalId":234433,"journal":{"name":"2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126612528","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
Super-Resolution of Face Images Based on Adaptive Markov Network 基于自适应马尔可夫网络的人脸图像超分辨率
2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System Pub Date : 2007-12-16 DOI: 10.1109/SITIS.2007.107
D. Huang, J. Siebert, W. Cockshott, Yijun Xiao
{"title":"Super-Resolution of Face Images Based on Adaptive Markov Network","authors":"D. Huang, J. Siebert, W. Cockshott, Yijun Xiao","doi":"10.1109/SITIS.2007.107","DOIUrl":"https://doi.org/10.1109/SITIS.2007.107","url":null,"abstract":"Adopting a patch-based Markov network as the fundamental mechanism, we first propose a patch-position constraint operation for searching matched patches in the training dataset to increase the probability value of observation function. For the hidden nodes, based on the first advantage and discovering that horizontal features of the face is more significant than vertical features visually, we create a local compatibility-checking algorithm which uses the most compatible neighboring patches along horizontal dimension of the face to synthesize the super-resolved outcome. Experiments demonstrate the effectiveness of the proposed algorithm.","PeriodicalId":234433,"journal":{"name":"2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116604348","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
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