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2010 20th International Conference on Pattern Recognition最新文献

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Object Tracking by Structure Tensor Analysis 基于结构张量分析的目标跟踪
2010 20th International Conference on Pattern Recognition Pub Date : 2010-10-07 DOI: 10.1109/ICPR.2010.637
M. Donoser, Stefan Kluckner, H. Bischof
{"title":"Object Tracking by Structure Tensor Analysis","authors":"M. Donoser, Stefan Kluckner, H. Bischof","doi":"10.1109/ICPR.2010.637","DOIUrl":"https://doi.org/10.1109/ICPR.2010.637","url":null,"abstract":"Covariance matrices have recently been a popular choice for versatile tasks like recognition and tracking due to their powerful properties as local descriptor and their low computational demands. This paper outlines similarities of covariance matrices to the well-known structure tensor. We show that the generalized version of the structure tensor is a powerful descriptor and that it can be calculated in constant time by exploiting the properties of integral images. To measure the similarities between several structure tensors, we describe an approximation scheme which allows comparison in a Euclidean space. Such an approach is also much more efficient than the common, computationally demanding Riemannian Manifold distances. Experimental evaluation proves the applicability for the task of object tracking demonstrating improved performance compared to covariance tracking.","PeriodicalId":309591,"journal":{"name":"2010 20th International Conference on Pattern Recognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129294300","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 New Application of MEG and DTI on Word Recognition MEG和DTI在单词识别中的新应用
2010 20th International Conference on Pattern Recognition Pub Date : 2010-10-07 DOI: 10.1109/ICPR.2010.605
Lu Meng, J. Xiang, Dazhe Zhao, Hong Zhao
{"title":"A New Application of MEG and DTI on Word Recognition","authors":"Lu Meng, J. Xiang, Dazhe Zhao, Hong Zhao","doi":"10.1109/ICPR.2010.605","DOIUrl":"https://doi.org/10.1109/ICPR.2010.605","url":null,"abstract":"This paper presented a novel application of Magneto encephalography (MEG) and diffusion tensor image (DTI) on word recognition, in which the spatiotemporal signature and the neural network of brain activation associated with word recognition were investigated. The word stimuli consisted of matched and mismatched words, which were visually and acoustically presented simultaneously. Twenty participants were recruited to distinguish and gave different reactions to these two types of stimuli. The neural activations caused by their reactions were recorded by MEG system and 3T magnetic DTI scanner. Virtual sensor technique and wavelet beam former source analysis, which were state-of-the-art methods, were used to study the MEG and DTI data. Three responses were evoked in the MEG waveform and M160 was identified in the left temporal-occipital junction. All the results coincided with the previous studies’ conclusions, which indicated that the integration of virtual sensor and wavelet beam former were effective techniques in analyzing the MEG and DTI data.","PeriodicalId":309591,"journal":{"name":"2010 20th International Conference on Pattern Recognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129454862","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
Automatic Face Replacement in Video Based on 2D Morphable Model 基于二维变形模型的视频人脸自动替换
2010 20th International Conference on Pattern Recognition Pub Date : 2010-10-07 DOI: 10.1109/ICPR.2010.551
Feng Min, N. Sang, Zhefu Wang
{"title":"Automatic Face Replacement in Video Based on 2D Morphable Model","authors":"Feng Min, N. Sang, Zhefu Wang","doi":"10.1109/ICPR.2010.551","DOIUrl":"https://doi.org/10.1109/ICPR.2010.551","url":null,"abstract":"This paper presents an automatic face replacement approach in video based on 2D morphable model. Our approach includes three main modules: face alignment, face morph, and face fusion. Given a source image and target video, the Active Shape Models (ASM) is adopted to source image and target frames for face alignment. Then the source face shape is warped to match the target face shape by a 2D morphable model. The color and lighting of source face are adjusted to keep consistent with those of target face, and seamlessly blended in the target face. Our approach is fully automatic without user interference, and generates natural and realistic results.","PeriodicalId":309591,"journal":{"name":"2010 20th International Conference on Pattern Recognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116317958","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
A New Rotation Feature for Single Tri-axial Accelerometer Based 3D Spatial Handwritten Digit Recognition 基于单三轴加速度计的三维空间手写体数字识别新旋转特征
2010 20th International Conference on Pattern Recognition Pub Date : 2010-10-07 DOI: 10.1109/ICPR.2010.1025
Yang Xue, Lianwen Jin
{"title":"A New Rotation Feature for Single Tri-axial Accelerometer Based 3D Spatial Handwritten Digit Recognition","authors":"Yang Xue, Lianwen Jin","doi":"10.1109/ICPR.2010.1025","DOIUrl":"https://doi.org/10.1109/ICPR.2010.1025","url":null,"abstract":"A new rotation feature extracted from tri-axial acceleration signals for 3D spatial handwritten digit recognition is proposed. The feature can effectively express the clockwise and anti-clockwise direction changes of the users’ movement while writing in a 3D space. Based on the rotation feature, an algorithm for 3D spatial handwritten digit recognition is presented. First, the rotation feature of the handwritten digit is extracted and coded. Then, the normalized edit distance between the digit and class model is computed. Finally, classification is performed using Support Vector Machine (SVM). The proposed approach outperforms time-domain features with a 22.12% accuracy improvement, peak-valley features with a 12.03% accuracy improvement, and FFT features with a 3.24% accuracy improvement, respectively. Experimental results show that the proposed approach is effective.","PeriodicalId":309591,"journal":{"name":"2010 20th International Conference on Pattern Recognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129065226","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 Empirical Study of Feature Extraction Methods for Audio Classification 音频分类特征提取方法的实证研究
2010 20th International Conference on Pattern Recognition Pub Date : 2010-10-07 DOI: 10.1109/ICPR.2010.1111
Charles Parker
{"title":"An Empirical Study of Feature Extraction Methods for Audio Classification","authors":"Charles Parker","doi":"10.1109/ICPR.2010.1111","DOIUrl":"https://doi.org/10.1109/ICPR.2010.1111","url":null,"abstract":"With the growing popularity of video sharing web sites and the increasing use of consumer-level video capture devices, new algorithms are needed for intelligent searching and indexing of such data. The audio from these video streams is particularly challenging due to its low quality and high variability. Here, we perform a broad empirical study of features used for intelligent audio processing. We perform experiments on a dataset of 200 consumer videos over which we attempt to detect 10 semantic audio concepts.","PeriodicalId":309591,"journal":{"name":"2010 20th International Conference on Pattern Recognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115633513","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
Robust Color Image Segmentation through Tensor Voting 基于张量投票的鲁棒彩色图像分割
2010 20th International Conference on Pattern Recognition Pub Date : 2010-10-07 DOI: 10.1109/ICPR.2010.823
R. Moreno, M. García, D. Puig
{"title":"Robust Color Image Segmentation through Tensor Voting","authors":"R. Moreno, M. García, D. Puig","doi":"10.1109/ICPR.2010.823","DOIUrl":"https://doi.org/10.1109/ICPR.2010.823","url":null,"abstract":"This paper presents a new method for robust color image segmentation based on tensor voting, a robust perceptual grouping technique used to extract salient information from noisy data. First, an adaptation of tensor voting to both image denoising and robust edge detection is applied. Second, pixels in the filtered image are classified into likely-homogeneous and likely-inhomogeneous by means of the edginess maps generated in the first step. Third, the likely-homosgeneous pixels are segmented through an efficient graph-based segmenter. Finally, a modified version of the same graph-based segmenter is applied to the likely-inhomogeneous pixels in order to obtain the final segmentation. Experiments show that the proposed algorithm has a better performance than the state-of-the-art.","PeriodicalId":309591,"journal":{"name":"2010 20th International Conference on Pattern Recognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115702952","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
Are Correlation Filters Useful for Human Action Recognition? 相关过滤器对人类行为识别有用吗?
2010 20th International Conference on Pattern Recognition Pub Date : 2010-10-07 DOI: 10.1109/ICPR.2010.639
Saad Ali, S. Lucey
{"title":"Are Correlation Filters Useful for Human Action Recognition?","authors":"Saad Ali, S. Lucey","doi":"10.1109/ICPR.2010.639","DOIUrl":"https://doi.org/10.1109/ICPR.2010.639","url":null,"abstract":"It has been argued in recent work that correlation filters are attractive for human action recognition from videos. Motivation for their employment in this classification task lies in their ability to: (i) specify where the filter should peak in contrast to all other shifts in space and time, (ii) have some degree of tolerance to noise and intra-class variation (allowing learning from multiple examples), and (iii) can be computed deterministically with low computational overhead. Specifically, Maximum Average Correlation Height (MACH) filters have exhibited encouraging results~cite{Mikel} on a variety of human action datasets. Here, we challenge the utility of correlation filters, like the MACH filter, in these circumstances. First, we demonstrate empirically that identical performance can be attained to the MACH filter by simply taking the~emph{average} of the same action specific training examples. Second, we characterize theoretically and empirically under what circumstances a MACH filter would become equivalent to the average of the action specific training examples. Based on this characterization, we offer an alternative type of filter, based on a discriminative paradigm, that circumvent the inherent limitations of correlation filters for action recognition and demonstrate improved action recognition performance.","PeriodicalId":309591,"journal":{"name":"2010 20th International Conference on Pattern Recognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125427524","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
Using Moments on Spatiotemporal Plane for Facial Expression Recognition 基于时空面矩的面部表情识别
2010 20th International Conference on Pattern Recognition Pub Date : 2010-10-07 DOI: 10.1109/ICPR.2010.927
Yi Ji, Khalid Idrissi
{"title":"Using Moments on Spatiotemporal Plane for Facial Expression Recognition","authors":"Yi Ji, Khalid Idrissi","doi":"10.1109/ICPR.2010.927","DOIUrl":"https://doi.org/10.1109/ICPR.2010.927","url":null,"abstract":"In this paper, we propose a novel approach to capture the dynamic deformation caused by facial expressions. The proposed method is concentrated on the spatiotemporal plane which is not well explored. It uses the moments as features to describe the movements of essential components such as eyes and mouth on vertical time plane. The system we developed can automatically recognize the expression on images as well as on image sequences. The experiments are performed on 348 sequences from 95 subjects in Cohn-Kanade database and obtained good results as high as 96.1% in 7-class recognition for frames and 98.5% in 6-class for sequences.","PeriodicalId":309591,"journal":{"name":"2010 20th International Conference on Pattern Recognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121882900","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
Fast Fingerprint Retrieval with Line Detection 快速指纹检索与线检测
2010 20th International Conference on Pattern Recognition Pub Date : 2010-10-07 DOI: 10.1109/ICPR.2010.771
Huicheng Lian
{"title":"Fast Fingerprint Retrieval with Line Detection","authors":"Huicheng Lian","doi":"10.1109/ICPR.2010.771","DOIUrl":"https://doi.org/10.1109/ICPR.2010.771","url":null,"abstract":"In this paper, a retrieval method is proposed for audio and video fingerprinting systems by adopting a line detection technique. To achieve fast retrieval, the ‘lines’ are generated from sub-fingerprints of query and database, and the non-candidate lines are filtered out. So, the distance between query and refers can be calculated fast. To demonstrate the superiority of this method, the audio fingerprints and video fingerprints are generated for comparisons. The experimental results indicate that the proposed method outperforms the direct hashing method.","PeriodicalId":309591,"journal":{"name":"2010 20th International Conference on Pattern Recognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121128560","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
Quantification of Subcellular Molecules in Tissue Microarray 组织芯片中亚细胞分子的定量
2010 20th International Conference on Pattern Recognition Pub Date : 2010-10-07 DOI: 10.1109/ICPR.2010.624
A. Can, M. Bello, M. Gerdes
{"title":"Quantification of Subcellular Molecules in Tissue Microarray","authors":"A. Can, M. Bello, M. Gerdes","doi":"10.1109/ICPR.2010.624","DOIUrl":"https://doi.org/10.1109/ICPR.2010.624","url":null,"abstract":"Quantifying expression levels of proteins with sub cellular resolution is critical to many applications ranging from biomarker discovery to treatment planning. In this paper, we present a fully automated method and a new metric that quantifies the expression of target proteins in immunohisto-chemically stained tissue microarray (TMA) samples. The proposed metric is superior to existing intensity or ratio-based methods. We compared performance with the majority decision of a group of 19 observers scoring estrogen receptor (ER) status, achieving a detection rate of 96% with 90% specificity. The presented methods will accelerate the processes of biomarker discovery and transitioning of biomarkers from research bench to clinical utility.","PeriodicalId":309591,"journal":{"name":"2010 20th International Conference on Pattern Recognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116666758","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
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