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检索条件"任意字段=International Workshop on Intelligent Computing in Pattern Analysis/Synthesis, IWICPAS 2006"

共 26 条记录，以下是11-20 订阅

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Scale space based grammar for hand detection 1

引用

international workshop on intelligent Computer in pattern analysis/synthesis

作者： Prokaj, Jan da Vitoria Lobo, Niels Univ Cent Florida Orlando FL 32816 USA

ISBN: (数字)9783540375982

ISBN: (纸本)354037597X

For detecting difficult objects, like hands, we present an algorithm that uses tokens and a grammar. Tokens are found by employing a new scale space edge detector that finds scale invariant features at object boundaries. We begin by constructing the scale space. Then we find edges at each scale and flatten the scale space to one edge image. To detect a hand we define a hand pattern grammar using curve tokens for finger tips and wedges, and line tokens. We identify a hand pattern by parsing these tokens using a graph based algorithm. We show and discuss the results of this algorithm on a database of hand images.

关键词： pattern matching

来源：评论

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Efficient and robust segmentations based on eikonal and diffusion PDEs 1

引用

international workshop on intelligent Computer in pattern analysis/synthesis

作者： Peny, Bertrand Unal, Gozde Slabaugh, Greg Fang, Tong Alvino, Christopher Siemens Corp Res Intelligent Vis & Reasoning Princeton NJ 08540 USA Univ Penn Dept Radiol Sect Biomed Image Anal Philadelphia PA 19104 USA

ISBN: (数字)9783540375982

ISBN: (纸本)354037597X

In this paper, we present efficient and simple image segmentations based on the solution of two separate Eikonal equations, each originating from a different region. Distance functions from the interior and exterior regions are computed, and final segmentation labels are determined by a competition criterion between the distance functions. We also consider applying a diffusion partial differential equation (PDE) based method to propagate information in a manner inspired by the information propagation feature of the Eikonal equation. Experimental results are presented in a particular medical image segmentation application, and demonstrate the proposed methods:

关键词： Image segmentation

来源：评论

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Speaker identification and verification using support vector machines and sparse kernel logistic regression 1

引用

international workshop on intelligent Computer in pattern analysis/synthesis

作者： Katz, Marcel Krueger, Sven E. Schaffoener, Martin Andelic, Edin Wendemuth, Andreas Univ Magdeburg IESK D-39106 Magdeburg Germany

ISBN: (数字)9783540375982

ISBN: (纸本)354037597X

In this paper we investigate two discriminative classification approaches for frame-based speaker identification and verification, namely Support Vector Machine (SVM) and Sparse Kernel Logistic Regression (SKLR). SVMs have already shown good results in regression and classification in several fields of pattern recognition as well as in continuous speech recognition. While the non-probabilistic output of the SVM has to be translated into conditional probabilities, the SKLR produces the probabilities directly. In speaker identification and verification experiments both discriminative classification methods outperform the standard Gaussian Mixture Model (GMM) system on the POLYCOST database.

关键词： pattern recognition

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Identifying single good clusters in data sets 1

引用

international workshop on intelligent Computer in pattern analysis/synthesis

作者： Klawonn, Frank Univ Appl Sci Braunschweig Wolfenbuettel Dept Comp Sci D-38302 Wolfenbuttel Germany

ISBN: (数字)9783540375982

ISBN: (纸本)354037597X

Local patterns in the form of single clusters are of interest in various areas of data mining. However, since the intention of cluster analysis is a global partition of a data set into clusters, it is not suitable to identify single clusters in a large data set where the majority of the data can not be assigned to meaningful clusters. This paper presents a new objective function-based approach to identify a single good cluster in a data set making use of techniques known from prototype-based, noise and fuzzy clustering. The proposed method can either be applied in order to identify single clusters or to carry out a standard cluster analysis by finding clusters step by step and determining the number of clusters automatically in this way.

关键词： cluster analysis local pattern discovery

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Audio brush: A tool for computer-assisted smart audio editing

Audio brush: A tool for computer-assisted smart audio editin...

引用

1st ACM workshop on Audio and Music computing for Multimedia, AMCMM'06, co-located with the 2006 ACM international Multimedia Conference

作者： Boogaart, C.G.V.D. Lienhart, R. Multimedia Computing Lab. University of Augsburg 86159 Augsburg Germany

ISBN: (纸本)1595935010

Starting with a novel audio analysis and editing paradigm, a set of new and adaptive audio analysis and editing algorithms in the spectrogram are developed and integrated into a smart visual audio editing tool in a "what you see is what you hear" style. At the core of our algorithms and methods is a very?exible audio spectrogram that goes beyond FFT and Wavelets and supports manipulating a signal at any chosen time-frequency resolution:the Gabor analysis and synthesis. It gives maximum accuracy of the representation, is fully invertible, and enables resolution zooming. Simple audio objects are localized in time and frequency. They can easily be identified visually and selected by simple geometric selection masks such as rectangles, combs and polygons. For many audio objects, however the structures in the spectrogram are rather complex. Therefore, we present several intelligent and adaptive mask selection approaches. They are based on audio fingerprinting and visual pattern matching algorithms. Spectrograms of individually recorded sounds under controlled conditions or interactively selected in the current spectrogram can be regarded as visual and sophisticated templates. We discuss how to generate templates, how to find the best match out of a database and how to adapt the match to the sound which we want to edit. © 2006 ACM.

关键词： Audio equipment

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Automatic 3D face model reconstruction using one image 1

引用

international workshop on intelligent Computer in pattern analysis/synthesis

作者： Lu, Chen Jie, Yang Shanghai Jiao Tong Univ Inst Image Proc & Pattern Recognit Shanghai 200030 Peoples R China

ISBN: (数字)9783540375982

ISBN: (纸本)354037597X

In this paper, we reconstruct the corresponding 3D face model using only one 2D image. 3D feature points are obtained by optimally approximating 2D feature points set with defined similarity. Then, a shape model is reconstructed by the warp function algorithm. Finally, a realistic face model is created through texture mapping with registration method such as affine transform. Results show that the models we reconstruct are comparatively realistic, and they can be used for face recognition or computer animation. The computation speed is also satisfying.

关键词： face reconstruction similarity optimal approximation texture mapping

来源：评论

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Traffic video segmentation using adaptive-K Gaussian mixture model 1

引用

international workshop on intelligent Computer in pattern analysis/synthesis

作者： Tan, Rui Huo, Hong Qian, Jin Fang, Tao Shanghai Jiao Tong Univ Inst Image Proc & Pattern Recognit Shanghai 200240 Peoples R China

ISBN: (数字)9783540375982

ISBN: (纸本)354037597X

Video segmentation is an important phase in video based traffic surveillance applications. The basic task of traffic video segmentation is to classify pixels in the current frame to road background or moving vehicles, and casting shadows should be taken into account if exists. In this paper, a modified online EM procedure is proposed to construct Adaptive-K Gaussian Mixture Model (AKGMM) in which the dimension of the parameter space at each pixel can adaptively reflects the complexity of pattern at the pixel. A heuristic background components selection rule is developed to make pixel classification decision based on the proposed model. Our approach is demonstrated to be more adaptive, accurate and robust than some existing similar pixel modeling approaches through experimental results.

关键词： Image segmentation

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Kernel modified quadratic discriminant function for facial expression recognition 1

引用

international workshop on intelligent Computer in pattern analysis/synthesis

作者： Yang, Duan-Duan Jin, Lian-Wen Yin, Jun-Xun Zhen, Li-Xin Huang, Jian-Cheng S China Univ Technol Dept Elect & Commun Engn Guangzhou 510640 Peoples R China Motorola China Res Ctr Shanghai 210000 Peoples R China

ISBN: (数字)9783540375982

ISBN: (纸本)354037597X

The Modified Quadratic Discriminant Function was first proposed by Kimura et al to improve the performance of Quadratic Discriminant Function, which can be seen as a dot-product method by eigen-decompostion of the covariance matrix of each class. Therefore, it is possible to expand MQDF to high dimension space by kernel trick. This paper presents a new kernel-based method to pattern recognition, Kernel Modified Quadratic Discriminant Function (KMQDF), based on MQDF and kernel method. The proposed KMQDF is applied in facial expression recognition. JAFFE face database and the AR face database are used to test this algorithm. Experimental results show that the proposed KMQDF with appropriated parameters can outperform 1-NN, QDF, MQDF classifier.

关键词： pattern recognition

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Monitoring abnormal patterns with complex semantics over ICU data streams 1

引用

international workshop on intelligent Computer in pattern analysis/synthesis

作者： Zhou, Xinbiao Li, Hongyan Liu, Haibin Li, Meimei Tang, Lvan Fan, Yu Hu, Zijing Peking Univ Sch Elect Engn & Comp Sci Natl Lab Machine Percept Beijing 100871 Peoples R China

ISBN: (数字)9783540375982

ISBN: (纸本)354037597X

Monitoring abnormal patterns in data streams is an important research area for many applications. In this paper we present a new approach MAPS(Monitoring Abnormal patterns over data Streams) to model and identify the abnormal patterns over the massive data streams. Compared with other data streams, ICU streaming data have their own features: pseudo-periodicity and polymorphism. MAPS first extracts patterns from the online arriving data streams and then normalizes them according to their pseudo-periodic semantics. Abnormal patterns will be detected if they are satisfied the predicates defined in the clinician-specifying normal patterns. At last, a real application demonstrates that MAPS is efficient and effective in several important aspects.

关键词： pattern recognition

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BTF modelling using BRDF texels 1

引用

international workshop on intelligent Computer in pattern analysis/synthesis

作者： Filip, J. Haindl, M. Acad Sci Czech Republ Inst Informat Theory & Automat Dept Pattern Recognit CR-18208 Prague Czech Republic

ISBN: (数字)9783540375982

ISBN: (纸本)354037597X

The highest fidelity representations of realistic real-world materials currently used comprise Bidirectional Texture Functions (BTF). The BTF is a six dimensional function depending on view and illumination directions as well as on planar texture coordinates. The huge size of such measurements, typically in the form of thousands of images covering all possible combinations of illumination and viewing angles, has prohibited their practical exploitation and obviously some compression and modelling method of these enormous BTF data spaces is inevitable. The proposed approach combines BTF spatial clustering with cluster index modelling by means of an efficient Markov random field model. This method allows to generate seamless cluster index of arbitrary size to cover large virtual 3D objects surfaces. The method represents original BTF data using a set of local spatially dependent Bidirectional Reflectance Distribution Function (BRDF) values which are combined according to synthesised cluster index and illumination / viewing directions. BTF data compression using this method is about 1 : 100 and their synthesis is very fast.

关键词： Functions

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