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Unsupervised Decomposition of Mixed Pixels Using the Maximum Entropy Principle 基于最大熵原理的混合像素的无监督分解
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.1142
Lidan Miao, H. Qi, H. Szu
{"title":"Unsupervised Decomposition of Mixed Pixels Using the Maximum Entropy Principle","authors":"Lidan Miao, H. Qi, H. Szu","doi":"10.1109/ICPR.2006.1142","DOIUrl":"https://doi.org/10.1109/ICPR.2006.1142","url":null,"abstract":"Due to the wide existence of mixed pixels, the derivation of constituent components (endmembers) and their proportions (abundances) at subpixel scales has become an important research topic. In this paper, we propose a novel unsupervised decomposition method based on the classical maximum entropy principle, termed uMaxEnt. The algorithm integrates a global least square error-based endmember detection and a per-pixel maximum entropy learning to find the most possible proportions. We apply the proposed method to the subject of spectral unmixing. The experimental results obtained from both simulated and real hyper-spectral data demonstrate the effectiveness of the uMaxEnt method","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"14 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":"128067086","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: 13
Object Tracking Using Globally Coordinated Nonlinear Manifolds 全局协调非线性流形的目标跟踪
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.885
Che-Bin Liu, Ruei-Sung Lin, Ming-Hsuan Yang, N. Ahuja, S. Levinson
{"title":"Object Tracking Using Globally Coordinated Nonlinear Manifolds","authors":"Che-Bin Liu, Ruei-Sung Lin, Ming-Hsuan Yang, N. Ahuja, S. Levinson","doi":"10.1109/ICPR.2006.885","DOIUrl":"https://doi.org/10.1109/ICPR.2006.885","url":null,"abstract":"We present a dynamic inference algorithm in a globally parameterized nonlinear manifold and demonstrate it on the problem of visual tracking. An appearance manifold is usually nonlinear, embedded in a high dimensional space, and can be approximated by a mixture of locally linear models. Existing methods for nonlinear dimensionality reduction, which map an appearance manifold to a single low dimensional coordinate system, preserve only spatial relationships among manifold points and render low dimensional embeddings rather than mapping functions. In this paper, we parameterize the mixture of linear appearance subspaces of an object in a global coordinate system, and apply it to visual tracking using a Rao-Blackwellized particle filter. Experimental results demonstrate that the proposed approach performs well on object tracking problem in scenes with significant clutter and temporary occlusions which pose difficulties for other methods","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"53 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":"125487485","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 Noise Robust Front-end for Speech Recognition Using Hough Transform and Cumulative Distribution Mapping 基于Hough变换和累积分布映射的语音识别噪声鲁棒前端
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.128
E. Choi
{"title":"A Noise Robust Front-end for Speech Recognition Using Hough Transform and Cumulative Distribution Mapping","authors":"E. Choi","doi":"10.1109/ICPR.2006.128","DOIUrl":"https://doi.org/10.1109/ICPR.2006.128","url":null,"abstract":"This paper describes a novel and noise robust front-end that employs the use of Hough transform for simultaneous frequency and temporal masking, together with cumulative distribution mapping of cepstral coefficients, for noisy speech recognition. Recognition experiments on the Aurora II connected digits database have revealed that the proposed front-end achieves an average digit recognition accuracy of 83.67%. Compared with the recognition results obtained by using the ETSI standard Mel-cepstral front-end, this accuracy represents a relative error rate reduction of around 58%","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"36 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":"125659919","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
A Fast and Efficient Ensemble Clustering Method 一种快速高效的集成聚类方法
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.62
P. Viswanath, K. Jayasurya
{"title":"A Fast and Efficient Ensemble Clustering Method","authors":"P. Viswanath, K. Jayasurya","doi":"10.1109/ICPR.2006.62","DOIUrl":"https://doi.org/10.1109/ICPR.2006.62","url":null,"abstract":"Ensemble of clustering methods is recently shown to perform better than conventional clustering methods. One of the drawback of the ensemble is, its computational requirements can be very large and hence may not be suitable for large data sets. The paper presents an ensemble of leaders clustering methods where the entire ensemble requires only a single scan of the data set. Further, the component leaders complement each other while deriving individual partitions. A heuristic based consensus method to combine the individual partitions is presented and is compared with a well known consensus method called co-association based consensus. Experimentally the proposed methods are shown to perform well","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":"127902251","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: 18
Monocular Vision Based SLAM for Mobile Robots 基于单目视觉的移动机器人SLAM
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.810
E. Mouragnon, M. Lhuillier, M. Dhome, F. Dekeyser, P. Sayd
{"title":"Monocular Vision Based SLAM for Mobile Robots","authors":"E. Mouragnon, M. Lhuillier, M. Dhome, F. Dekeyser, P. Sayd","doi":"10.1109/ICPR.2006.810","DOIUrl":"https://doi.org/10.1109/ICPR.2006.810","url":null,"abstract":"This paper describes a new vision based method for the simultaneous localization and mapping of mobile robots. The only data used is a video input from a moving calibrated monocular camera. From the detection and matching of interest points in images at video rate, robust estimates of the camera poses are computed in real-time and a 3D map of the environment is reconstructed. The computed 3D structure is constantly refined thanks to the introduction of a fast and local bundle adjustment method that makes this approach particularly accurate and reliable. Actually, this method can be seen as a new visual tool that may be used in conjunction with usual systems (GPS, inertia sensors, etc) in SLAM applications","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"34 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":"127980147","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: 69
A Person and Context Specific Approach for Skin Color Classification 一种针对人与环境的肤色分类方法
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.151
M. Wimmer, B. Radig, M. Beetz
{"title":"A Person and Context Specific Approach for Skin Color Classification","authors":"M. Wimmer, B. Radig, M. Beetz","doi":"10.1109/ICPR.2006.151","DOIUrl":"https://doi.org/10.1109/ICPR.2006.151","url":null,"abstract":"Skin color is an important feature of faces. Various applications benefit from robust skin color detection. Depending on camera settings, illumination, shadows, people's tans, and ethnic groups skin color looks differently, which is a challenging aspect for detecting it automatically. In this paper, we present an approach that uses a high level vision module to detect an image specific skin color model. This model is then used to adapt parametric skin color classifiers to the processed image. This approach is capable to distinguish skin color from extremely similar colors, such as lip color or eyebrow color. Its high speed and high accuracy make it appropriate for real time applications such as face tracking and recognition of facial expressions","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"16 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":"127983434","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: 26
Extending the Depth of Field in a Compound-Eye Imaging System with Super-Resolution Reconstruction 利用超分辨率重建扩展复眼成像系统的景深
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.519
Wai-San Chan, E. Lam, M. Ng
{"title":"Extending the Depth of Field in a Compound-Eye Imaging System with Super-Resolution Reconstruction","authors":"Wai-San Chan, E. Lam, M. Ng","doi":"10.1109/ICPR.2006.519","DOIUrl":"https://doi.org/10.1109/ICPR.2006.519","url":null,"abstract":"Optical device miniaturization is highly desirable in many applications. Direct down-scaling of traditional imaging system is one approach, but the extent to which it can be minimized is limited by the effect of diffraction. Compound-eye imaging system, which utilizes multiple microlenses in image capture is a promising alternative. In this paper, we explore the possibility of an incorporation of phase masks in such a system to extend the depth of field. Simulation experiments are conducted to verify the feasibility of the system","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"7 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":"121789306","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
Blind Phase-Amplitude Modulation Classification with Unknown Phase Offset 相位偏移未知的盲相位调幅分类
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.333
M. Wong, A. Nandi
{"title":"Blind Phase-Amplitude Modulation Classification with Unknown Phase Offset","authors":"M. Wong, A. Nandi","doi":"10.1109/ICPR.2006.333","DOIUrl":"https://doi.org/10.1109/ICPR.2006.333","url":null,"abstract":"This paper first discusses the maximum likelihood (ML) classifier for automatic classification of digital modulations. The classifier is optimum for classification of phase-amplitude modulated signals under ideal environment. However, this is not the case in the presence of phase offset owing to inaccurate estimation. In this paper, we propose a novel non-coherent ML classifier to mitigate the effect phase offset. The non-coherent ML classifier adopts a pre-classification phase correction stage through a closed form estimator based on higher order statistics. Experimental results show improvement of classification accuracy at reasonable signal to noise ratio","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"38 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":"115840408","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
A Model-based Approach for Rigid Object Recognition 一种基于模型的刚性物体识别方法
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.103
Chee Boon Chong, T. Tan, F. Lim
{"title":"A Model-based Approach for Rigid Object Recognition","authors":"Chee Boon Chong, T. Tan, F. Lim","doi":"10.1109/ICPR.2006.103","DOIUrl":"https://doi.org/10.1109/ICPR.2006.103","url":null,"abstract":"Most object recognition systems require large databases of real images for classifier training. To collect real images for this purpose is a difficult and expensive process. This paper introduces a unified framework based on the creation and use of synthetic images for training various classifiers to achieve recognition of real-world objects. A 3D model of the object (i.e. trolley in this case) is constructed from a minimum of two photographs. The constructed 3D model is used to automatically generate the relevant synthetic images that are subsequently used to train the Adaboost and support vector machine-based recognition systems. Experimental results obtained are very encouraging suggesting that synthetically generated images generated by our approach can augment the real training samples used in current recognition systems","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"4 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":"115876792","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
Recognition of lung lobes and its application to the bronchial structure analysis 肺叶的识别及其在支气管结构分析中的应用
18th International Conference on Pattern Recognition (ICPR'06) Pub Date : 2006-08-20 DOI: 10.1109/ICPR.2006.972
T. Kitasaka, Y. Nakada, K. Mori, Y. Suenaga, M. Mori, H. Takabatake, H. Natori
{"title":"Recognition of lung lobes and its application to the bronchial structure analysis","authors":"T. Kitasaka, Y. Nakada, K. Mori, Y. Suenaga, M. Mori, H. Takabatake, H. Natori","doi":"10.1109/ICPR.2006.972","DOIUrl":"https://doi.org/10.1109/ICPR.2006.972","url":null,"abstract":"This paper describes a method for recognizing the lung lobes and its application to analysis of the bronchial structure. Analysis of the lung structure is one of important functions in a computer aided diagnosis system for chest CT data. Since the lung is composed of five lobes, analysis of the lung requires recognition of each lobe area. Thin membranes, called interlobar pleura, exist between lobes. Their CT values are higher than those of the lung parenchyma on CT images. Therefore, the proposed method extracts interlobar pleura regions and interpolates the regions by fitting quadratic surfaces. Then, lung regions are divided into lobes using fitted surfaces. From the obtained lung lobe regions and the bronchial tree data extracted beforehand, each bronchial branch is classified into the lobe to which it belongs. The proposed method was applied to fourteen cases of 3D chest CT images. The experimental results showed that lung regions were satisfactorily divided into lobes and that most bronchi were classified into lobes to which they belong","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"17 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":"132048869","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
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