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检索条件"机构=Computer Vision and Pattern Recognition"

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3D and Infrared Face Reconstruction from RGB data using Canonical Correlation Analysis

3D and Infrared Face Reconstruction from RGB data using Cano...

引用

International Conference on pattern recognition

作者： M. Reiter R. Donner G. Langs H. Bischof Pattern Recognition and Image Processing Group Vienna University of Technology Austria Graz University of Technology Institute for Computer Graphics and Vision Austria

In this paper, we apply a multiple regression method based on canonical correlation analysis (CCA) to face data modelling. CCA is a factor analysis method which exploits the correlation between two high dimensional signals. We first use CCA to perform 3D face reconstruction and in a separate application we predict near-infrared (NIR) face texture. In both cases, the input data are color (RGB) face images. Experiments show, that due to the correlation between input and output signal, only a small number of canonical factors are needed to describe the functional relation of RGB images to the respective output (NIR images and 3D depth maps) with reasonable accuracy

关键词： Shape Face detection Lighting Image reconstruction Image analysis Image databases pattern analysis Rendering (computer graphics) Image color analysis pattern recognition

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A New DCT-FFT Fusion Based Method for Caption and Scene Text Classification in Action Video Images 2nd

A New DCT-FFT Fusion Based Method for Caption and Scene Text...

引用

2nd International Conference on pattern recognition and Artificial Intelligence, ICPRAI 2020

作者： Nandanwar, Lokesh Shivakumara, Palaiahnakote Manna, Suvojit Pal, Umapada Lu, Tong Blumenstein, Michael Faculty of Computer Science and Information Technology University of Malayasia Kuala Lumpur Malaysia Department of Computer Science and Engineering Jalpaiguri Government Engineering College Jalpaiguri India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India National Key Lab for Novel Software Technology Nanjing University Nanjing China University of Technology Sydney Ultimo Australia

ISBN: (纸本)9783030598297

Achieving better recognition rate for text in video action images is challenging due to multi-type texts with unpredictable backgrounds. We propose a new method for the classification of captions (which is edited text) and scene texts (which is part of an image in video images of Yoga, Concert, Teleshopping, Craft, and Recipe classes). The proposed method introduces a new fusion criterion-based on DCT and Fourier coefficients to extract features that represent good clarity and visibility of captions to separate them from scene texts. The variances for coefficients of corresponding pixels of DCT and Fourier images are computed to derive the respective weights. The weights and coefficients are further used to generate a fused image. Furthermore, the proposed method estimates sparsity in Canny edge image of each fused image to derive rules for classifying caption and scene texts. Lastly, the proposed method is evaluated on images of five above-mentioned action image classes to validate the derived rules. Comparative studies with the state-of-the-art methods on the standard databases show that the proposed method outperforms the existing methods in terms of classification. The recognition experiments before and after classification show that the recognition performance rate improves significantly after classification. © 2020, Springer Nature Switzerland AG.

关键词： Classification (of information)

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An Approach of Strike-Through Text Identification from Handwritten Documents

An Approach of Strike-Through Text Identification from Handw...

引用

International Workshop on Frontiers in Handwriting recognition

作者： Chandranath Adak Bidyut B. Chaudhuri Dept. of Computer Science & Engg University of Kalyani West Bengal India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

A handwritten document may contain strike-through texts. If such texts are fed into an OCR system, the output will be garbage. In this paper, we propose a scheme to detect such strike-through texts/words. Using a graph based model, we represent a textual connected component as a graph. The start/end and intersection points of the ink-strokes of a component are marked as graph nodes. There exists an edge between two nodes if they are connected by object (ink) pixels. By eliminating parallel edges and self loops we obtain a simple, undirected, edge-weighted graph of the text-component. The edge-weight is found by adding horizontal/vertical moves weighted by 1 and diagonal moves weighted by √2. In this graph, we find the shortest path which is nearly as long as the width of the text component and maintains a reasonable degree of straightness. This path, if exist, is identified as the strike-through line. Here we deal with handwritten documents in English, Bengali and Devanagari script. Our approach delivers fairly good results.

关键词： Handwriting recognition Hidden Markov models Character recognition Optical character recognition software Image edge detection Ink Databases

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A Two Stage Approach for Handwritten Malayalam Character recognition

A Two Stage Approach for Handwritten Malayalam Character Rec...

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International Workshop on Frontiers in Handwriting recognition

作者： Jomy John K.V. Pramod Kannan Balakrishnan Bidyut B. Chaudhuri Dept. of Computer Applications Cochin University of Science and Technology Kochi India Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India

Handwritten character recognition is still a research challenge in OCR discipline, especially for Indian scripts. This paper deals with handwritten Malayalam, a major Indian script, where past work considered a small subset of characters only. In this paper we deal with complete set of basic characters, vowel and consonant signs and compound characters that may be present in the script. Here the recognition task is more difficult because of large numbers of classes and high interclass similarity. To tackle the problem, we proposed a two-stage approach. The first stage is a group classifier, where a group consists of similar characters and those that misclassify among themselves. In the second stage, a character assigned to a group in the first stage is classified to a particular character class. The proposed scheme is more accurate and efficient than a single stage scheme.

关键词： Compounds Character recognition Support vector machines Shape Handwriting recognition Feature extraction Databases

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ISIgraphy: A tool for online handwriting sample database generation

ISIgraphy: A tool for online handwriting sample database gen...

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National Conference on computer vision, pattern recognition, Image Processing and Graphics (NCVPRIPG)

作者： Arindam Das Ujjwal Bhattacharya Department of Computer Science & Engineering Narula Institute of Technology Kolkata India Computer Vision and Pattern Recognition Unit Indian Statistical Institute (ISI) Kolkata India

Online handwriting recognition research has recently received significant thrust. Specifically for Indian scripts, handwriting recognition has not been focused much till in the near past. However, due to generous Government funding through the group on Technology Development for Indian Languages (TDIL) of the Ministry of Communication & Information Technology (MC&IT), Govt. of India, research in this area has received due attention and several groups are now engaged in research and development works for online handwriting recognition in different Indian scripts. An extensive bottleneck of the desired progress in this area is the difficulty of collection of large sample databases of online handwriting in various scripts. Towards the same, recently a user-friendly tool on Android platform has been developed to collect data on handheld devices. This tool is called ISIgraphy and has been uploaded in the Google Play for free download. This application is designed well enough to store handwritten data samples in large scales in user-given file names for distinct users. Its use is script independent, meaning that it can collect and store handwriting samples written in any language, not necessarily an Indian script. It has an additional module for retrieval and display of stored data. Moreover, it can directly send the collected data to others via electronic mail.

关键词： Databases Handwriting recognition Character recognition Handheld computers Benchmark testing Text recognition

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A New Method for Handwritten Scene Text Detection in Video

A New Method for Handwritten Scene Text Detection in Video

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International Workshop on Frontiers in Handwriting recognition

作者： Palaiahnakote Shivakumara Anjan Dutta Umapada Pal Chew Lim Tan School of Computing National University of Singapore Singapore Computer Vision Center Universitat Authnòma de Barcelona Barcelona Spain Computer Vision and Pattern Recognition Unit Indian Statistical Institute India

There are many video images where hand written text may appear. Therefore handwritten scene text detection in video is essential and useful for many applications for efficient indexing, retrieval etc. Also there are many video frames where text line may be multi-oriented in nature. To the best of our knowledge there is no work on handwritten text detection in video, which is multi-oriented in nature. In this paper, we present a new method based on maximum color difference and boundary growing method for detection of multi-oriented handwritten scene text in video. The method computes maximum color difference for the average of R, G and B channels of the original frame to enhance the text information. The output of maximum color difference is fed to a K-means algorithm with K = 2 to separate text and non-text clusters. Text candidates are obtained by intersecting the text cluster with the Sobel output of the original frame. To tackle the fundamental problem of different orientations and skews of handwritten text, boundary growing method based on a nearest neighbor concept is employed. We evaluate the proposed method by testing on our own handwritten text database and publicly available video data (Hua's data). Experimental results obtained from the proposed method are promising.

关键词： Pixel Image edge detection Image color analysis Graphics Clustering algorithms Image resolution Measurement

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Robust stereo on multiple resolutions

Robust stereo on multiple resolutions

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International Conference on pattern recognition

作者： C. Menard A. Leonardis Department for Pattern Recognition and Image Processing Technical University of of Vienna Vienna Austria Computer and InformationScience. Computer Vision Laboratory University of Ljubljana Ljubljana Slovenia

Stereo computation is one of the vision problems where the presence of outliers cannot be neglected. Most standard algorithms make unrealistic assumptions about noise distributions, which leads to erroneous results that cannot be corrected in subsequent postprocessing stages. In this paper we present a modification of the standard area-based correlation approach so that it can tolerate a significant number of outliers. The approach exhibits a robust behavior not only in the presence of mismatches but also in the case of depth discontinuities. The confidence measure of the correlation and the number of outliers provide two complementary sources of information which, when implemented in a multiresolution framework, result in a robust and efficient method. We present the results of this approach on a number of synthetic and real images.

关键词： Stereo vision computer vision Noise robustness Information resources Correlation pattern recognition Image processing Layout Cameras Laboratories

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Proceedings of 3rd International Conference on computer vision and Image Processing 1

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丛书名： Advances in Intelligent Systems and Computing

2020年

作者： Bidyut B. Chaudhuri Masaki Nakagawa Pritee Khanna Sanjeev Kumar

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ICDAR2015 Competition on Video Script Identification (CVSI 2015)

ICDAR2015 Competition on Video Script Identification (CVSI 2...

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International Conference on Document Analysis and recognition

作者： Nabin Sharma Ranju Mandal Rabi Sharma Umapada Pal Michael Blumenstein School of Information and Communication Technology Griffith University Queensland Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9781479918065

This paper presents the final results of the ICDAR 2015 Competition on Video Script Identification. A description and performance of the participating systems in the competition are reported. The general objective of the competition is to evaluate and benchmark the available methods on word-wise video script identification. It also provides a platform for researchers around the globe to particularly address the video script identification problem and video text recognition in general. The competition was organised around four different tasks involving various combinations of scripts comprising tri-script and multiscript scenarios. The dataset used in the competition comprised ten different scripts. In total, six systems were received from five participants over the tasks offered. This report details the competition dataset specifications, evaluation criteria, summary of the participating systems and their performance across different tasks. The systems submitted by Google Inc. were the winner of the competition for all the tasks, whereas the systems received from Huazhong University of Science and Technology (HUST) and computer vision Center (CVC) were very close competitors.

关键词： Video scripts identification multi-lingual OCR multi-lingual video-text competition

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Indian multi-script full pin-code string recognition for postal automation

Indian multi-script full pin-code string recognition for pos...

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ICDAR2009 - 10th International Conference on Document Analysis and recognition

作者： Pal, U. Roy, R.K. Roy, K. Kimura, F. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-108 India Dept. of Comp. Sc. West Bengal State University Barasat India Graduate School of Engg. Mie University 1577 Kurimamachiya-cho Tsu 514-8507 Japan

ISBN: (纸本)9780769537252

Under three-language formula, the destination address block of postal document of an Indian state is generally written in three languages: English, Hindi and the State official language. Because of inter-mixing of these scripts in postal address writings, it is very difficult to identify the script by which a pin-code is written. Also, because of the writing style of different individuals some of the digits in a pin-code string may touch with its neighboring digits. Accurate segmentation of such touching components into individual digits is a difficult task. To avoid such difficulties, in this paper we proposed a tri-lingual (English, Hindi and Bangla) 6-digit full pin-code string recognition. We obtained 99.01% reliability from our proposed system when error and rejection rates are 0.83% and 15.27%, respectively. © 2009 IEEE.

关键词： Codes (symbols)

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