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检索条件"任意字段=International Conference on Soft Computing and Pattern Recognition"

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Web Multimedia Object Clustering via Information Fusion

Web Multimedia Object Clustering via Information Fusion

引用

international conference on Document Analysis and recognition

作者： Wenting Lu Lei Li Tao Li Honggang Zhang Jun Guo Pattern Recognition and Intelligence System Laboratory Beijing University of Posts and Telecommunications Beijing China School of Computing and Information Sciences Florida International University Miami FL USA

Multimedia information plays an increasingly important role in humans daily activities. Given a set of web multimedia objects (images with corresponding texts), a challenging problem is how to group these images into several clusters using the available information. Previous researches focus on either adopting individual information, or simply combining image and text information together for clustering. In this paper, we propose a novel approach (Dynamic Weighted Clustering) to separate images under the "supervision" of text descriptions, Also, we provide a comparative experimental investigation on utilizing text and image information to tackle web image clustering. Empirical experiments on a manually collected web multimedia object (related to the events after disasters) dataset are conducted to demonstrate the efficacy of our proposed method.

关键词： Feature extraction Symmetric matrices Clustering algorithms Accuracy Multimedia communication Semantics Weight measurement

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Historical Document Layout Analysis Competition

Historical Document Layout Analysis Competition

引用

international conference on Document Analysis and recognition

作者： A. Antonacopoulos C. Clausner C. Papadopoulos S. Pletschacher Pattern Recognition and Image Analysis (PRImA) Research Laboratory School of Computing Science and Engineering University of Salford Greater Manchester UK

ISBN: (纸本)9781457713507

This paper presents an objective comparative evaluation of layout analysis methods for scanned historical documents. It describes the competition (modus operandi, dataset and evaluation methodology) held in the context of ICDAR2011 and the international Workshop on Historical Document Imaging and Processing (HIP2011), presenting the results of the evaluation of four submitted methods. A commercial state-of-the-art system is also evaluated for comparison. Two scenarios are reported in this paper, one evaluating the ability of methods to accurately segment regions and the other evaluating the whole pipeline of segmentation and region classification (with a text extraction goal). The results indicate that there is a convergence to a certain methodology with some variations in the approach. However, there is still a considerable need to develop robust methods that deal with the idiosyncrasies of historical documents.

关键词： Layout Particle separators Text analysis Performance evaluation Libraries Image segmentation Corporate acquisitions

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Support Vector Machine Classifier for pattern recognition

Support Vector Machine Classifier for Pattern Recognition

引用

international conference on Informatics and Computational Intelligence (ICI)

作者： Mohammad Farhan Ghulam Kassem Mujeeb Abdullah Siddique Akbar Institute of Engineering and Computing Sciennces University of Science and Technology Bannu Pakistan Shanghai Instt. of Microsystems and I.T (SIMIT) Intl Centre of Wireless Collaborative Research Shanghai China Institute of Engineering and Technology (IET) University of Science and Technology Bannu Pakistan Institute of Engineering and Technology (IET) Gomal University D.I.Khan Pakistan

Automatiuc speech recognition is carried out by Mel-frequency cepstral coefficient (MFCC). Linearly-spaced at low and logarithmic-spaced filters at higher frequencies are used to capture the characteristics of speech. Multi-layer perceptrons (MLP) approximate continuous and non-linear functions. High dimensional patterns are not permitted due to eigen-decomposition in high dimensional image space and degeneration of scattering matrices in small size sample. Generalization, dimensionality reduction and maximizing the margins are controlled by minimizing weight vectors. Results show good pattern by SVM algorithm with Mercer kernel.

关键词： Support vector machines Kernel Feature extraction Speech Vectors Covariance matrix Mel frequency cepstral coefficient

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Interpreting presence sensor data and looking for similarities between homes using cluster analysis

Interpreting presence sensor data and looking for similariti...

引用

international conference on Pervasive computing Technologies for Healthcare, PervasiveHealth

作者： John Loane Brian O'Mullane Brennon Bortz R. Benjamin Knapp CASALA Dundalk Institute of Technology Dundalk Ireland

In order to model older people's behaviour in the home we must first understand it. In this paper we examine data from eight purpose-built aware homes over a six-month period, looking at presence in rooms to try to determine patterns amongst the older residents. We look for homes that have similar movement patterns using cluster analysis. We also examine how movement over days clusters within individual homes. Our analysis begins to show the possibilities of distinguishing between residents in their homes based on patterns of movement.

关键词： Clustering algorithms Aging Databases pattern recognition Firing Electricity Layout

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Restoration of Arbitrarily Warped Historical Document Images Using Flow Lines

Restoration of Arbitrarily Warped Historical Document Images...

引用

international conference on Document Analysis and recognition

作者： Maryam Rahnemoonfar Apostolos Antonacopoulos Pattern Recognition and Image Analysis (PRImA) Research Laboratory School of Computing Science and Engineering University of Salford UK

ISBN: (纸本)9781457713507

Historical documents frequently suffer from arbitrary geometric distortions (warping and folds) due to storage conditions, use and to, some extent, the printing process of the time. In addition, page curl can be prominent due to the scanning technique used. Such distortions adversely affect OCR and print-on-demand quality. Previous approaches to geometric restoration either focus only on the correction of page curl or require supplementary information obtained by additional scanning hardware - not practical for existing scans. This paper presents a new approach to detect and restore arbitrary warping and folds, in addition to page curl. Warped text lines and the smooth deformation between them are precisely modelled as primary and secondary flow lines that are then restored to their original linear shape. Preliminary, but representative, experimental results, in comparison to a leading page curl removal method and an industry-standard commercial system, demonstrate the effectiveness of the proposed method.

关键词： Text analysis

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Robust human pose estimation from corrupted images with partial occlusions and noise pollutions

Robust human pose estimation from corrupted images with part...

引用

IEEE international conference on Granular computing (GRC)

作者： Guoliang Lu Mineichi Kudo Jun Toyama Laboratory of pattern recognition and machine learning Graduate School of Information Science and Technology Hokkaido University Sapporo Japan

Robust human pose estimation from the given visual observations has attracted many attentions in the past two decades. However, this problem is still challenging due to the situation that observations are often corrupted with partial occlusions or noise pollutions or both in real-world applications. In this paper, we propose to estimate human pose by using robust silhouette matching in original rectangle-coordinate space. In addition, human action model is employed to determinate reasonable matching results. Experimental results on robustness sequence of Weizman dataset reveal that our proposed approach can estimate human pose robustly and reasonably when pose observations are corrupted with partial occlusions or noise pollutions.

关键词： Estimation Legged locomotion Humans Testing Computational modeling Feature extraction Robustness

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Feature selection through gravitational search algorithm

Feature selection through gravitational search algorithm

引用

international conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： J. P. Papa A. Pagnin S. A. Schellini A. Spadotto R. C. Guido M. Ponti G. Chiachia A. X. Falcão Department of Computing UNESP-Universidade Estadual Paulista Brazil Institute of Mathematics and Computer Science s University of São Paulo Brazil Institute of Computing State University of Campinas-UNICAMP Brazil

ISBN: (纸本)9781457705380

In this paper we deal with the problem of feature selection by introducing a new approach based on Gravitational Search Algorithm (GSA). The proposed algorithm combines the optimization behavior of GSA together with the speed of Optimum-Path Forest (OPF) classifier in order to provide a fast and accurate framework for feature selection. Experiments on datasets obtained from a wide range of applications, such as vowel recognition, image classification and fraud detection in power distribution systems are conducted in order to asses the robustness of the proposed technique against Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and a Particle Swarm Optimization (PSO)-based algorithm for feature selection.

关键词： Mathematical model Equations Accuracy Force Algorithm design and analysis pattern recognition Principal component analysis

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A New Gradient Based Character Segmentation Method for Video Text recognition

A New Gradient Based Character Segmentation Method for Video...

引用

international conference on Document Analysis and recognition

作者： Palaiahnakote Shivakumara Souvik Bhowmick Bolan Su Chew Lim Tan Umapada Pal School of Computing National University of Singapore Singapore Computer Vision and Pattern Recognition Unit Indian Statistical Unit Kolkata India

The current OCR cannot segment words and characters from video images due to complex background as well as low resolution of video images. To have better accuracy, this paper presents a new gradient based method for words and character segmentation from text line of any orientation in video frames for recognition. We propose a Max-Min clustering concept to obtain text cluster from the normalized absolute gradient feature matrix of the video text line image. Union of the text cluster with the output of Canny operation of the input video text line is proposed to restore missing text candidates. Then a run length algorithm is applied on the text candidate image for identifying word gaps. We propose a new idea for segmenting characters from the restored word image based on the fact that the text height difference at the character boundary column is smaller than that of the other columns of the word image. We have conducted experiments on a large dataset at two levels (word and character level) in terms of recall, precision and f-measure. Our experimental setup involves 3527 characters of English and Chinese, and this dataset is selected from TRECVID database of 2005 and 2006.

关键词： Text recognition Character recognition Image segmentation Accuracy Optical character recognition software Image recognition

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A systematic approach to adaptive activity modeling and discovery in smart homes

A systematic approach to adaptive activity modeling and disc...

引用

international conference on BioMedical Engineering and Informatics (BMEI)

作者： Liming Chen George Okeyo Hui Wang Roy Sterritt Chris Nugent Computer Science Research Institute School of Computing and Mathematics University of Ulster Newtownabbey UK

Activity modelling and discovery plays a critical role in smart home based assisted living. Existing approaches to pattern recognition using data-intensive analysis suffers from various drawbacks. To address these shortcomings, this paper introduces a novel ontology-based approach to activity modelling, activity discovery and evolution. In this approach, activity modelling is undertaken through ontological engineering by leveraging domain knowledge and heuristics. The generated activity models evolve from the initial “seed” activity models through continuous activity discovery and learning. Activity discovery is performed through ontological reasoning. The paper describes the approach in the context of smart home with special emphases placed on activity discovery algorithms and evolution mechanism. The approach has been implemented in a feature-rich assistive living system in which new daily activities can be detected and further used to evolve the underlying activity models.

关键词： Ontologies Adaptation models pattern recognition Cognition Smart homes Humans

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Incorporating Prior-Knowledge in Support Vector Machines by Kernel Adaptation

Incorporating Prior-Knowledge in Support Vector Machines by ...

引用

international conference on Tools for Artificial Intelligence (ICTAI)

作者： Antoine Veillard Daniel Racoceanu Stephane Bressan School of Computing National University of Singapore Singapore IPAL CNRS Singapore

SVMs with the general purpose RBF kernel are widely considered as state-of-the-art supervised learning algorithms due to their effectiveness and versatility. However, in practice, SVMs often require more training data than readily available. Prior-knowledge may be available to compensate this shortcoming provided such knowledge can be effectively passed on to SVMs. In this paper, we propose a method for the incorporation of prior-knowledge via an adaptation of the standard RBF kernel. Our practical and computationally simple approach allows prior-knowledge in a variety of forms ranging from regions of the input space as crisp or fuzzy sets to pseudo-periodicity. We show that this method is effective and that the amount of required training data can be largely decreased, opening the way for new usages of SVMs. We propose a validation of our approach for pattern recognition and classification tasks with publicly available datasets in different application domains.

关键词： Kernel Training Labeling Support vector machines Cancer Training data pattern recognition

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