发布求助
文献互助 智能选刊 最新文献

2009 Seventh International Conference on Advances in Pattern Recognition最新文献

筛选
英文 中文
Histogram-Based Partial Differential Equation for Object Tracking 基于直方图的目标跟踪偏微分方程
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.75
P. Li, Lijuan Xiao
{"title":"Histogram-Based Partial Differential Equation for Object Tracking","authors":"P. Li, Lijuan Xiao","doi":"10.1109/ICAPR.2009.75","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.75","url":null,"abstract":"Traditional object tracking based on color histograms can only represent objects with rectangles or ellipses, thus having very limited ability to follow objects with complex shapes or with highly non-rigid motion. In addressing this problem, we formulate histogram-based tracking as a functional optimization problem based on Jesson-Shannon divergence that is bounded, symmetric and a true metric. Optimization of the functional consists in searching for a candidate image region of possibly very complex shape, whose color distribution is the most similar to the known, target distribution. By using two different techniques of shape derivative and variational derivative (in section 2 and appendix respectively), we derive the partial differential equation (PDE) that describes the evolution of the object contour. Level set algorithm is used to compute the solution of the PDE. Experiments show that the proposed work is globally convergent and can track objects with complex shapes and/or with highly non-rigid motion.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125413369","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
Color Image Retrieval Using M-Band Wavelet Transform Based Color-Texture Feature 基于m波段小波变换颜色纹理特征的彩色图像检索
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.34
M. Kundu, Priyank Bagrecha
{"title":"Color Image Retrieval Using M-Band Wavelet Transform Based Color-Texture Feature","authors":"M. Kundu, Priyank Bagrecha","doi":"10.1109/ICAPR.2009.34","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.34","url":null,"abstract":"Feature Extraction algorithm is a very important component of any retrieval scheme. We propose M-band Wavelet Transform based feature extraction algorithm in this paper. The MxM sub-bands are used as primitive features, over which energies computed in a neighborhood are taken as the features for each pixel of the image. These features are clustered using FCM to obtain image signature for similarity matching using the Earth Mover's Distance. The results obtained were compared with MPEG-7 content descriptor based system and found to be superior.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129396046","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
Distraction Free Evolution of Active Contours 活动轮廓的无干扰进化
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.18
V. Srikrishnan, S. Chaudhuri
{"title":"Distraction Free Evolution of Active Contours","authors":"V. Srikrishnan, S. Chaudhuri","doi":"10.1109/ICAPR.2009.18","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.18","url":null,"abstract":"We propose a novel energy term to make the curve evolution quite robust to spurious edges. The physical intuition behind the formulation is that an object edge is generally continuous, but it could be composed of weak and strong segments. We then formulate the energy term which depends on a second order measure defined on the contour. Minimisation of this energy term  yields a space varying curvature based  curve evolution equation. An added advantage of the formulation is that this term also acts as the regularising term for smoothing the curve evolution. The proposed term can therefore be used in conjunction with any of the numerous gradient based active contour models. For our experimentation purpose, we have used the well-known gradient vector  force model as the external force. We have performed a number of experiments on images and obtained good results.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124781827","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
Region Based Image Fusion for Detection of Ewing Sarcoma 基于区域的图像融合检测Ewing肉瘤
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.33
T. Zaveri, M. Zaveri
{"title":"Region Based Image Fusion for Detection of Ewing Sarcoma","authors":"T. Zaveri, M. Zaveri","doi":"10.1109/ICAPR.2009.33","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.33","url":null,"abstract":"In the medical image processing different sources of images are providing complementary information so fusion of different source images will give more details for diagnosis of patients. In this paper an automatic region based image fusion algorithm is proposed which is applied on the registered Magnetic Resonance (MR) image of human brain. The aim of this paper is to detect all the information required for accurate diagnosis of a brain tumor namely, Ewing sarcoma which is simultaneously not available in individual MR images. The proposed region based image fusion method is applied on two types of MR sequence images to extract useful information which is than compared with different pixel based algorithm and the performance of these fusion schemes are evaluated using standard quality assessment parameters. From the analysis of quality assessment parameters we found that our scheme provides better result compared to pixel based fusion scheme. The resultant fused image is assessed and validated by radiologist.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121821790","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: 12
A Thinning-free Algorithm for Straight Edge Detection in a Gray-scale Image 灰度图像直线边缘检测的无稀疏算法
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.74
Sanjoy Pratihar, Partha Bhowmick
{"title":"A Thinning-free Algorithm for Straight Edge Detection in a Gray-scale Image","authors":"Sanjoy Pratihar, Partha Bhowmick","doi":"10.1109/ICAPR.2009.74","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.74","url":null,"abstract":"An efficient algorithm to detect the straight edges present in a gray-scale image is proposed.Algorithms to detect curvilinear edges (of possibly uneven thickness) and algorithms to segment a one-pixel thick digital curve into a sequence of straight pieces are found in the literature in several varieties and in several paradigms. However, to the best of our knowledge, there exists no algorithm till date that can detect straight edges in a gray-scale image without thinning. The proposed algorithm uses the novel idea of exponential averaging to achieve a carry-forward of previous edge strengths along the traversed straight edge. The process is computationally attractive, since the underlying operations at an edge point effectively reduce to one right shift and one integer addition. The straightness of an edge is verified from classical chain code properties realizable by simple integer operations, thereby making the algorithm easy for implementation and fast in execution. Experimental results demonstrate its efficiency and robustness.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122933984","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
Ordering and Elimination Based Component Learning Method 基于排序和消去的构件学习方法
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.103
Sheetal Reddy Pamudurthy, C. Sekhar
{"title":"Ordering and Elimination Based Component Learning Method","authors":"Sheetal Reddy Pamudurthy, C. Sekhar","doi":"10.1109/ICAPR.2009.103","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.103","url":null,"abstract":"In this paper, we propose a component learning method to learn a set of Gaussian components that fit the given data distribution. An ordering and visualization technique called OPTICS and tests of multinormality are used in this method. We consider the applications of the proposed method to the tasks of classification and clustering. Here, the components are used to define a feature space to which the data points are transformed. In that feature space, classification is performed using linear support vector machines and clustering is performed using support vector clustering. The performance of the component learning method and its application to classification and clustering is demonstrated on synthetic datasets.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121020359","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
Hierarchical Local Maps for Robust Approximate Nearest Neighbor Computation 鲁棒近似最近邻计算的层次局部映射
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.99
Pratyush Bhatt, A. Namboodiri
{"title":"Hierarchical Local Maps for Robust Approximate Nearest Neighbor Computation","authors":"Pratyush Bhatt, A. Namboodiri","doi":"10.1109/ICAPR.2009.99","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.99","url":null,"abstract":"In this paper, we propose a novel method for fast nearest neighbors retrieval in non-Euclidean and non-metric spaces. We organize the data into a hierarchical fashion that preserves the local similarity structure. A method to find the approximate nearest neighbor of a query is proposed, that drastically reduces the total number of explicit distance measures that need to be computed. The representation overcomes the restrictive assumptions in traditional manifold mappings, while enabling fast nearest neighbor's search. Experimental results on the Unipen and CASIA Iris datasets clearly demonstrates the advantages of the approach and improvements over state of the art algorithms. The algorithm can work in batch mode as well as in sequential mode and is highly scalable.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122329334","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
Semantic Grouping of Shots in a Video Using Modified K-Means Clustering 基于改进k -均值聚类的视频镜头语义分组
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.35
Partha Pratim Mohanta, S. Saha
{"title":"Semantic Grouping of Shots in a Video Using Modified K-Means Clustering","authors":"Partha Pratim Mohanta, S. Saha","doi":"10.1109/ICAPR.2009.35","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.35","url":null,"abstract":"Semantic grouping of the shots in a video can bethought of as first step towards scene detection. It also facilitates the easy identification of visually similar scenes. Such grouping also help in the creation of semantic content table and efficient content browsing. In this work, we present an effective scheme to form such groupings. We address the important issue of representing a shot with the help of keyframes and other sampled frames from the shot. Finally, the content of the shot is denoted by the low-level feature vectors corresponding to the representative frames. Similar shots are grouped following a modified k-means clustering algorithm. Modifications have been incorporated to accommodate the differing roles played by the keyframes and sampled frames. We have carried out the experiment with different type of video data and result obtained is satisfactory.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126684698","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
Significance of Word and Syllable Level Information for Expressive Speech Processing 词和音节级信息对表达性语音处理的意义
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.47
K. S. Rao, S. Prasanna, T. V. Sagar
{"title":"Significance of Word and Syllable Level Information for Expressive Speech Processing","authors":"K. S. Rao, S. Prasanna, T. V. Sagar","doi":"10.1109/ICAPR.2009.47","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.47","url":null,"abstract":"In general, human beings make use of expressions (emotions) through speech, facial movements and gestures for conveying the crucial information. Mostly, expressions in speech can be attributed to longer segments, i.e., suprasegmental features also known to be prosodic features. In this paper we analyze the expressions in speech using prosodic features from utterance level, word level and syllable level. The emotions considered for the analysis are anger,compassion, happy and neutral. The prosodic features used in the analysis are duration, intonation (pitch) and energy. The analysis is performed on SUSE (Speech Under Simulated Emotion) database. The results of the analysis are used for synthesizing the expressions in neutral speech. The synthesis experiments using the features from utterance level to syllable level showed that a steady improvement in the quality of speech for the desired expressions.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129068961","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
Relevant and Redundant Feature Analysis with Ensemble Classification 集成分类的相关冗余特征分析
2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.36
Rakkrit Duangsoithong, T. Windeatt
{"title":"Relevant and Redundant Feature Analysis with Ensemble Classification","authors":"Rakkrit Duangsoithong, T. Windeatt","doi":"10.1109/ICAPR.2009.36","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.36","url":null,"abstract":"Feature selection and ensemble classification increase system efficiency and accuracy in machine learning, data mining and biomedical informatics. This research presents an analysis of the effect of removing irrelevant and redundant features with ensemble classifiers using two datasets from UCI machine learning repository. Accuracy and computational time were evaluated by four base classifiers; NaiveBayes, Multilayer Perceptron, Support Vector Machines and Decision Tree. Eliminating irrelevant features improves accuracy and reduces computational time while removing redundant features reduces computational time and reduces accuracy of the ensemble.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116817641","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: 24
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信