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2008 Chinese Conference on Pattern Recognition最新文献

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Multi-Class Classification Based on Fisher Criteria with Weighted Distance 基于费雪标准和加权距离的多类分类法
2008 Chinese Conference on Pattern Recognition Pub Date : 2008-10-31 DOI: 10.1109/CCPR.2008.17
Meng Ao, S.Z. Li
{"title":"Multi-Class Classification Based on Fisher Criteria with Weighted Distance","authors":"Meng Ao, S.Z. Li","doi":"10.1109/CCPR.2008.17","DOIUrl":"https://doi.org/10.1109/CCPR.2008.17","url":null,"abstract":"Linear discriminant analysis (LDA) is an efficient dimensionality reduction algorithm. In this paper we propose a new Fisher criteria with weighted distance (FCWWD) to find an optimal projection for multi-class classification tasks. We replace the classical linear function with a nonlinear weight function to describe the distances between samples in Fisher criteria. What's more, we give a new algorithm based on this criteria along with a theoretical explanation that our algorithm benefits from an approximation of the ROC optimization. Experimental results demonstrate the efficiency of our method to improve the multi-class classification performance.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127877693","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
2D-ONPP: Two Dimensional Extension of Orthogonal Neighborhood Preserving Projections for Face Recognition 2D-ONPP:用于人脸识别的正交邻域保持投影的二维扩展
2008 Chinese Conference on Pattern Recognition Pub Date : 2008-10-31 DOI: 10.1109/CCPR.2008.48
Chuan-Xian Ren, D. Dai
{"title":"2D-ONPP: Two Dimensional Extension of Orthogonal Neighborhood Preserving Projections for Face Recognition","authors":"Chuan-Xian Ren, D. Dai","doi":"10.1109/CCPR.2008.48","DOIUrl":"https://doi.org/10.1109/CCPR.2008.48","url":null,"abstract":"This paper considers the problem of orthogonal neighborhood preserving projections (ONPP) in two-dimensional sense. Recently, ONPP was proposed as a projection based dimensionality reduction technique, attempting to preserve both the intrinsic neighborhood geometry of the data samples and the global geometry. Concerned with two dimensional data, such as face images, often vectorized for ONPP algorithm to find the intrinsic manifold structure. However, ONPP can't be implemented effectively due to the high dimensionality. Therefore, a novel method, two-dimensional orthogonal neighborhood preserving projections (2D-ONPP), directly based on 2D image matrices instead of ID vectors, is proposed for face recognition society. It finds an embedding that preserves neighborhood geometrical features and detects the intrinsic image manifold structure. The performance of the proposed algorithm is compared with existing 2D-PCA and ONPP methods on ORL and Yale B databases. Experimental results show the efficient computation performance and the competitive average recognition rate of our 2D algorithm.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115365863","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
Uyghur Character Recognition Basing on Neural Network 基于神经网络的维吾尔文字识别
2008 Chinese Conference on Pattern Recognition Pub Date : 2008-10-31 DOI: 10.1109/CCPR.2008.77
Yan Zhou, A. Halidan
{"title":"Uyghur Character Recognition Basing on Neural Network","authors":"Yan Zhou, A. Halidan","doi":"10.1109/CCPR.2008.77","DOIUrl":"https://doi.org/10.1109/CCPR.2008.77","url":null,"abstract":"In this paper contrapose the characteristic of Uyghur character, propose a new method for Uyghur character recognition basing on neural network. The means utilizes projection to isolate the letters of the connected character field, then put pretreatment Uyghur character block image mode classify using neural network, extraction of outer features. It indicates that we can get relatively satisfying results.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116346758","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
A New Method for Facial Beauty Assessment 一种新的面部美容评价方法
2008 Chinese Conference on Pattern Recognition Pub Date : 2008-10-31 DOI: 10.1109/CCPR.2008.62
Yili Chen, Lian-Wen Jin, Zetao Chen, Xutao Li, C. Huang, Zhenhua Feng
{"title":"A New Method for Facial Beauty Assessment","authors":"Yili Chen, Lian-Wen Jin, Zetao Chen, Xutao Li, C. Huang, Zhenhua Feng","doi":"10.1109/CCPR.2008.62","DOIUrl":"https://doi.org/10.1109/CCPR.2008.62","url":null,"abstract":"Beauty is an abstract concept. How to quantify and evaluate beauty has always been a major concern among people. But few people adopt the way based on image processing and pattern recognition to assess beauty. For the first time, this paper proposed a way using computer image processing and pattern recognition for beauty assessment, and proposed a method based on the beauty- related feature points and the smoothness of the face skin. And by using the method of machine learning and pattern recognition, the paper formulates a standard to evaluate the beauty. The evaluation system proves to be simple, feasible and objective with regard to various testing samples.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114535248","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
Content-Based Semantic Indexing of Image using Fuzzy Support Vector Machines 基于内容的模糊支持向量机图像语义索引
2008 Chinese Conference on Pattern Recognition Pub Date : 2008-10-31 DOI: 10.1109/CCPR.2008.35
Jianming Li, Shuguang Huang, R. He, Kunming Qian
{"title":"Content-Based Semantic Indexing of Image using Fuzzy Support Vector Machines","authors":"Jianming Li, Shuguang Huang, R. He, Kunming Qian","doi":"10.1109/CCPR.2008.35","DOIUrl":"https://doi.org/10.1109/CCPR.2008.35","url":null,"abstract":"With the increasing amount of multimedia data, content-based image retrieval attracts many researchers of various fields in an effort to automate data analysis and indexing. In this paper, we propose a content-based semantic indexing method which annotates images automatically using concepts and textual description. In order to bridge the \"semantic gap\" between the low-level descriptors and the high-level semantic concepts of an image, we introduce a 3-level pyramid and combine the color, texture and edge features for each level. Fuzzy support vector machine (FSVM) is employed for building the concept model and calculates the likelihood of an image to a model. We index the images with concepts according to the likelihood between an image and the concept model. Experiments show that our method has good accuracy in semantic indexing of images.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114670131","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
A Feature Fusion Algorithm for Human Matching between Non-Overlapping Cameras 一种非重叠摄像机间人体匹配的特征融合算法
2008 Chinese Conference on Pattern Recognition Pub Date : 2008-10-31 DOI: 10.1109/CCPR.2008.23
Xiaowei Lv, Qingjie Kong, Yuncai Liu
{"title":"A Feature Fusion Algorithm for Human Matching between Non-Overlapping Cameras","authors":"Xiaowei Lv, Qingjie Kong, Yuncai Liu","doi":"10.1109/CCPR.2008.23","DOIUrl":"https://doi.org/10.1109/CCPR.2008.23","url":null,"abstract":"Human matching is fundamental in human tracking over non-overlapping cameras. Fusing multiple features is an efficient way to increase the ratio of matching. In this paper, we present an algorithm of iterative widening fusion (IWF) to fuse the multiple features, including color histogram, UV chromaticity, major color spectrum histogram and scale-invariant features (SIFT). Also, the Bayesian framework, as a classical fusion method, is compared with the IWF algorithm. The experimental results indicated that the IWF algorithm obtained the matching accuracy better than Bayesian framework in most cases.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133038027","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 Efficient Web Document Classification Algorithm Based on LPP and SVM 基于LPP和SVM的高效Web文档分类算法
2008 Chinese Conference on Pattern Recognition Pub Date : 2008-10-31 DOI: 10.1109/CCPR.2008.91
Ziqiang Wang, Yuxun Liu, Xia Sun
{"title":"An Efficient Web Document Classification Algorithm Based on LPP and SVM","authors":"Ziqiang Wang, Yuxun Liu, Xia Sun","doi":"10.1109/CCPR.2008.91","DOIUrl":"https://doi.org/10.1109/CCPR.2008.91","url":null,"abstract":"With the explosive growth of World Wide Web, it is of great importance to develop methods for the automatic classifying of large collections of documents. To efficiently tackle this problem, a novel document classification algorithm based on locality pursuit projection (LPP) and SVM is proposed in this paper. The high-dimensional document space are first mapped into lower-dimensional space with LPP, the SVM is then used to classify the documents into semantically different classes. Experimental results show that the proposed algorithm achieves much better performance than other classification algorithms.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115787026","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
Detection of Intima-Media Layer of Common Carotid Artery with Dynamic Programming Based Active Contour Model 基于动态规划的活动轮廓模型检测颈总动脉内膜-中膜
2008 Chinese Conference on Pattern Recognition Pub Date : 2008-10-31 DOI: 10.1109/CCPR.2008.78
Ge Liu, Bo Wang, D.C. Liu
{"title":"Detection of Intima-Media Layer of Common Carotid Artery with Dynamic Programming Based Active Contour Model","authors":"Ge Liu, Bo Wang, D.C. Liu","doi":"10.1109/CCPR.2008.78","DOIUrl":"https://doi.org/10.1109/CCPR.2008.78","url":null,"abstract":"Ultrasound measurements of the carotid artery wall in image are usually obtained by manually tracing. In this paper, we present an automatic segmentation method to detect the intima-media layer in far wall of the common carotid artery. The energy definition of active contour model is used. Different from the traditional approach applied in snake techniques, we treat the optimization problem as finding the shortest cost path in a directed graph. Dynamic programming is selected to search the shortest path. The external force and internal force in snake model are modified to be suitable for our approach. To reduce the effect of speckle noise, a new method in speckle reduction by anisotropic diffusion is adopted. At last, we compare the result of our method with other two methods. Results show that our method can detect the intimal and adventitia layers as well as other methods, the two layers will not cross with each other as traditional dynamic programming does. Moreover, our method needs less manual input than others.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116392256","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: 11
A Semi-Supervised Learning Based Relevance Feedback Algorithm in Content-Based Image Retrieval 基于半监督学习的相关反馈算法在基于内容的图像检索中的应用
2008 Chinese Conference on Pattern Recognition Pub Date : 2008-10-31 DOI: 10.1109/CCPR.2008.37
Zhi-Ping Luo, Xing-Ming Zhang
{"title":"A Semi-Supervised Learning Based Relevance Feedback Algorithm in Content-Based Image Retrieval","authors":"Zhi-Ping Luo, Xing-Ming Zhang","doi":"10.1109/CCPR.2008.37","DOIUrl":"https://doi.org/10.1109/CCPR.2008.37","url":null,"abstract":"As a useful solution for address the faultage between image features and semanteme, relevance feedback (RF) became an effective approach to boost image retrieval. In supervised-based machine learning algorithm, insufficient Labeled training data and the unlabeled data in one RF circle can not represent scatter of features space for all irrelevant images, such algorithm used for CBIR did not show a high performance. As a research hot point, semi-supervised, it can utilize unlabeled data to estimate model of RF so that boost the retrieval performance. This paper proposed a new algorithm for RF: make use of expectation maximization (EM) to learn RBF function for RBF neutral network, integrated active learning to void a local value EM learned, and reduce iterations of feedback, as a result this algorithm learned a RF model based on RBF. Experience indicated that: compare to EM and Bayes, efficiency of learner is improved, user's query concept is grasped quickly.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124946311","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
3D Affine Moment Invariants for Surfaces 曲面的三维仿射不变量
2008 Chinese Conference on Pattern Recognition Pub Date : 2008-10-31 DOI: 10.1109/CCPR.2008.26
Dong Xu, Hua Li
{"title":"3D Affine Moment Invariants for Surfaces","authors":"Dong Xu, Hua Li","doi":"10.1109/CCPR.2008.26","DOIUrl":"https://doi.org/10.1109/CCPR.2008.26","url":null,"abstract":"A new kind of weighted surface moments is defined which can achieve affine invariance for unclosed surfaces. We can also select a corresponding point and build a pseudo-solid for surface and compute the affine volume moment invariants. We test the invariance of the two affine moment invariants on a 3D terrain map and a 3D face scan. The experimental result reveals that the weighted surface moment invariants are highly robust to shape deformations and numerical computation.","PeriodicalId":292956,"journal":{"name":"2008 Chinese Conference on Pattern Recognition","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117282332","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
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