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Using Various Types of Multimedia Resources to Train System for Automatic Transcription of Czech Historical Oral Archives

Using Various Types of Multimedia Resources to Train System ...

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17th international conference on image Analysis and processing (ICIAP)

作者： Chaloupka, Josef Nouza, Jan Kucharova, Michaela Tech Univ Liberec Inst Informat Technol & Elect Liberec 46117 Czech Republic

ISBN: (纸本)9783642411892;9783642411908

Historical spoken documents represent a unique segment of national cultural heritage. In order to disclose the large Czech Radio audio archive to research community and to public, we have been developing a system whose aim is to transcribe automatically the archive files, index them and make them searchable. The transcription of contemporary (1 or 2 decades old) documents is based on the lexicon and statistical language model (LM) built from a large amount of recent texts available in electronic form. From the older periods (before 1990), however, digital texts do not exist. Therefore, we needed a) to find resources that represent language of those times, b) to convert them from their original form to text, c) to utilize this text for creating epoch specific lexicons and LMs, and eventually, d) to apply them in the developed speech recognition system. In our case, the main resources included: scanned historical newspapers, shorthand notes from the national parliament and subtitles from retro TV programs. When converted into text, they allowed us to built a more appropriate lexicon and to produce a preliminary version of the transcriptions. These were reused for unsupervised retraining of the final LM. In this way, we significantly improved the accuracy of the automatically transcribed radio news broadcast in 1969-1989 era, from initial 83 % to 88 %.

关键词： historical audio archives speech-to-text transcription OCR lexicon building machine learning

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Hidden Markov Models with Graph Densities for Action recognition

Hidden Markov Models with Graph Densities for Action Recogni...

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international Joint conference on Neural Networks

作者： Michael Glodek Edmondo Trentin Friedhelm Schwenker Günther Palm Institute of Neural Information Processing University of Ulm Germany Dipartimento di Ingegneria dell' Infor mazione (DII) University of Siena Italy

ISBN: (纸本)9781467361279

Human action recognition in video streams is a fast developing field in pattern recognition and machine learning. Local image representations, e.g. space-time interest points [1], have proven to be the current most reliable choice of feature in sequences in which the region of interest is difficult to determine [2]. However, the question how to deal with more severe occlusions has large been ignored [2]. This work proposes a new approach which directly addresses heavy occlusions by modeling the skeleton-based features using a probability density functions (PDF) defined over graphs. We integrated the proposed density into an hidden Markov model (HMM) to model sequences of graphs of arbitrary sizes, i.e. occlusions setting may change over time. The approach is evaluated using a dataset embracing three action classes, studying six different types of occlusions (involving the removal of subgraphs from the graphical representation of action sequence). The presented study shows clearly that actions from even heavily occluded sequences can be reliably recognized.

关键词： Action recognition incomplete data

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1st international conference on Advanced machine learning Technologies and Applications, AMLTA 2012

1st International Conference on Advanced Machine Learning Te...

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ISBN: (纸本)9783642353253

The proceedings contain 59 papers. The special focus in this conference is on Rough Sets and Applications, machine learning in pattern recognition and image processing, machine learning in Multimedia Computing, Bioinformatics and Cheminformatics, Data Classification and Clustering, Cloud Computing and Recommender Systems, Case-Based Reasoning and Data processing, Authentication, Digital Forensics and Plagiarism Detection. The topics include: Rough sets-based machine learning over non-deterministic data;learning a table from a table with non-deterministic information;parameterised fuzzy Petri nets for approximate reasoning in decision support systems;rough sets-based rules generation approach;automatic color image segmentation based on illumination invariant and superpixelization;wavelet based statistical adapted local binary patterns for recognizing avatar faces;solving avatar captchas automatically;comparative analysis of image fusion techniques in remote sensing;density based fuzzy thresholding for image segmentation;subjectivity and sentiment analysis of Arabic;support vector machine approach for detecting events in video streams;study of feature categories for musical instrument recognition;a genetic-CBR approach for cross-document relationship identification;improved action recognition using an efficient boosting method;towards smart Egypt -the role of large scale WSNs;language for writing descriptors of outline shape of molecules;web service based approach for viral hepatitis ontology sharing and diagnosing;sampleboost for capsule endoscopy categorization and abnormality detection;advanced parallel genetic algorithm with gene matrix for global optimization;semi-possibilistic biclustering applied to discrete and continuous data;a comparative study of localization algorithms in WSNs;test cases automatic generator (TCAG);support vector machines with weighted powered kernels for data classification;an enhanced cloud-based view materialization approach for peer-to-

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Facial expression recognition using log-euclidean statistical shape models

Facial expression recognition using log-euclidean statistica...

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1st international conference on pattern recognition Applications and Methods, ICPRAM 2012

作者： Papiez, Bartlomiej W. Matuszewski, Bogdan J. Shark, Lik-Kwan Quan, Wei Applied Digital Signal and Image Processing Research Centre University of Central Lancashire PR1 2HE Preston United Kingdom

ISBN: (纸本)9789898425980

This paper presents a new method for facial expression modelling and recognition based on diffeomorphic image registration parameterised via stationary velocity fields in Log-Euclidean framework. The validation and comparison are done using different statistical shape models (SSM) built using the Point Distribution Model (PDM), velocity fields, and deformation fields. The obtained results show that the facial expression representation based on stationary velocity field can be successfully utilised in facial expression recognition, and this parameterisation produces higher recognition rate than the facial expression representation based on deformation fields.

关键词： Velocity

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Estimating planar structure in single images by learning from examples

Estimating planar structure in single images by learning fro...

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1st international conference on pattern recognition Applications and Methods, ICPRAM 2012

作者： Haines, Osian Calway, Andrew University of Bristol Bristol United Kingdom

ISBN: (纸本)9789898425980

Outdoor urban scenes typically contain many planar surfaces, which are useful for tasks such as scene reconstruction, object recognition, and navigation, especially when only a single image is available. In such situations the lack of 3D information makes finding planes difficult;but motivated by how humans use their prior knowledge to interpret new scenes with ease, we develop a method which learns from a set of training examples, in order to identify planar image regions and estimate their orientation. Because it does not rely explicitly on rectangular structures or the assumption of a'Manhattan world', our method can generalise to a variety of outdoor environments. From only one image, our method reliably distinguishes planes from non-planes, and estimates their orientation accurately;this is fast and efficient, with application to a real-time system in mind.

关键词： Real time systems

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The combination of hmax and hogs in an attention guided framework for object localization

The combination of hmax and hogs in an attention guided fram...

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1st international conference on pattern recognition Applications and Methods, ICPRAM 2012

作者： Brosch, Tobias Neumann, Heiko Institute of Neural Information Processing Ulm University Ulm Germany

ISBN: (纸本)9789898425980

Object detection and localization is a challenging task. Among several approaches, more recently hierarchical methods of feature-based object recognition have been developed and demonstrated high-end performance measures. Inspired by the knowledge about the architecture and function of the primate visual system, the computational HMAX model has been proposed. At the same time robust visual object recognition was proposed using feature distributions, e.g. histograms of oriented gradients (HOGs). Since both models build upon an edge representation of the input image, the question arises, whether one kind of approach might be superior to the other. Introducing a new biologically inspired attention steered processing framework, we demonstrate that the combination of both approaches gains the best results.

关键词： Object recognition

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Camera model identification using local binary patterns

Camera model identification using local binary patterns

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2012 13th IEEE international conference on Multimedia and Expo, ICME 2012

作者： Xu, Guanshuo Shi, Yun Qing New Jersey Institute of Technology Newark NJ United States

ISBN: (纸本)9781467316590

In digital image forensics, camera model identification seeks for the source camera model information from the given images under investigation. To achieve this goal, one of the popular approaches is extracting from the images under investigation certain statistical features that capture the difference caused by camera structure and various in-camera image processing algorithms, followed by machine learning and pattern recognition algorithms for similarity measures of extracted features. In this paper, we propose to use uniform gray-scale invariant local binary patterns (LBP) as statistical features. Considering 8-neighbor binary co-occurrence, three groups of 59 local binary patterns are extracted from the spatial domain of red and green color channels, their corresponding prediction-error arrays, and their 1st-level diagonal wavelet sub bands of each image, respectively. Multi-class support vector machines are built for classification of 18 camera models from âDresden image Database'. Compared with the results reported in literatures, the detection accuracy reported in this paper is higher. © 2012 IEEE.

关键词： Local binary pattern

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A relational distance-based framework for hierarchical image understanding

A relational distance-based framework for hierarchical image...

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1st international conference on pattern recognition Applications and Methods, ICPRAM 2012

作者： Antanas, Laura Van Otterlo, Martijn Jośe Oramas, M. Tuytelaars, Tinne De Raedt, Luc Katholieke Universiteit Leuven Leuven Belgium

ISBN: (纸本)9789898425980

Understanding images in terms of hierarchical and logical structures is crucial for many semantic tasks, including image retrieval, scene understanding and robot vision. This paper combines compositional hierarchies, qualitative spatial relations, relational instance-based learning and robust feature extraction in one framework. For each layer in the hierarchy, substructures in the images are detected, classified and then employed one layer up the hierarchy to obtain higher-level semantic structures, by making use of qualitative spatial relations. The approach is applied to street view images. We employ a four-layer hierarchy in which subsequently corners, windows and doors, and individual houses are detected.

关键词： Edge detection

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Facial Age Estimation Using Clustered Multi-task Support Vector Regression machine

Facial Age Estimation Using Clustered Multi-task Support Vec...

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21st international conference on pattern recognition (ICPR)

作者： Gao, Peter Xiang Univ Waterloo Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9784990644109;9781467322164

Automatic age estimation is the process of using a computer to predict the age of a person automatically based on a given facial image. While this problem has numerous real-world applications, the high variability of aging patterns and the sparsity of available data present challenges for model training. Here, instead of training one global aging function, we train an individual function for each person by a multi-task learning approach so that the variety of human aging processes can be modelled. To deal with the sparsity of training data, we propose a similarity measure for clustering the aging functions. During the testing stage, which involves a new person with no data used for model training, we propose a feature-based similarity measure for characterizing the test case. We conduct simulation experiments on the FG-NET and MORPH databases and compared our method with other state-of-the-art methods.

关键词： pattern recognition

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Optical Character recognition of Postmark Date Based on machine Vision

Optical Character Recognition of Postmark Date Based on Mach...

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2nd international conference on Engineering Materials, Energy, Management and Control

作者： You Fucheng Liu Yingjie Beijing Inst Graph Commun Informat & Mech Engn Sch Beijing Peoples R China

ISBN: (纸本)9783037853443

For the purpose of information management on postmark according to the date, the paper put forward a method of postmark date recognition based on machine vision, which could meet the demands of personal postmark collectors. On the basis of the relative theories of machine vision, image processing and pattern recognition, the overall process is introduced in the paper from postmark image acquisition to date recognition. Firstly, threshold method is used to generate binary image from smoothed postmark image. So region of date numbers could be extracted from binary image according to different region features. Then regions of date numbers which are connected or broken could be processed through mathematical morphology of binary image. Individual regions of date numbers are obtained for recognition. Finally, classification and pattern recognition based on support vector machine make date numbers classified and date recognition is implemented correctly.

关键词： machine vision postmark date mathematical morphology pattern recognition

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