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检索条件"机构=Computer Vision and Pattern"

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A New Symmetry Based on Proximity of Wavelet-Moments for Text Frame Classification in Video

A New Symmetry Based on Proximity of Wavelet-Moments for Tex...

引用

International Conference on pattern Recognition

作者： Palaiahnakote Shivakumara Anjan Dutta Chew Lim Tan Umapada Pal School of Computing National University of Singapore Singapore Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

This paper proposes the use of a new symmetry property based on proximity of the median moments in the wavelet domain. The method divides a given frame into 16 equally sized blocks to classify the true text frame. The average of high frequency subbands of a block is used for computing median moments to brighten the text pixel in a block of video frame. Then K-means clustering with K=2 is applied on the median moments of the block to classify it as a probable text block. For classified blocks, average wavelet median moments are computed for a sliding window. We introduce Max-Min cluster to classify the probable text pixel in each probable text block. The four quadrants are formed from the centroid of the probable text pixels. The new concept called symmetry is introduced to identify the true text block based on proximity between probable text pixels in each quadrant. If the frame produces at least one true text block, it is considered as a text frame otherwise a non-text frame. The method is tested on three datasets to evaluate the robustness of the method in classification of text frames in terms of recall and precision.

关键词： Pixel Chromium Feature extraction pattern recognition Robustness Silicon Classification algorithms

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Temporal Conditional Random Fields: A conditional state space predictor for visual tracking

Temporal Conditional Random Fields: A conditional state spac...

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Iranian Machine vision and Image Processing (MVIP)

作者： M. J. Shafiee Z. Azimifar P. Fieguth Computer Vision and Pattern Recognition Laboratory School of Electrical & Computer Engineering Shiraz University Shiraz Iran Systems Design Engineering University of Waterloo Waterloo Canada

We present a modified Temporal Conditional Random Fields framework for modeling and predicting object motion. To facilitate such a powerful graphical model with prediction and come up with a CRF-based predictor, we propose a set of new temporal relations for object tracking, with feature functions such as optical flow (calculated among consequent frames). We evaluate our proposed Temporal Conditional Random Field method with real and synthetic data sequences and will show that the TCRF prediction is nearly equivalent with result of template matching. Experimental results show that our proposed method estimates future target state with zero error until target dynamic changes. Our proposed modified CRF method with simple and easy to implement feature functions, can learn any target dynamic, thus, it can predict next state of target with zero error.

关键词： Computational modeling Hidden Markov models computer vision Predictive models Kalman filters Image motion analysis Dynamics

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Shape Code Based Word-Image Matching for Retrieval of Indian Multi-lingual Documents

Shape Code Based Word-Image Matching for Retrieval of Indian...

引用

International Conference on pattern Recognition

作者： Arundhati Tarafdar Ranju Mondal Srikanta Pal Umapada Pal Fumitaka Kimura Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Graduate School of Engineering Mie University Japan

ISBN: (纸本)9781424475421

In the current scenario retrieving information from document images is a challenging problem. In this paper we propose a shape code based word-image matching (word-spotting) technique for retrieval of multilingual documents written in Indian languages. Here, each query word image to be searched is represented by a primitive shape code using (i) zonal information of extreme points (ii) vertical shape based feature (iii) crossing count (with respect to vertical bar position) (iv) loop shape and position (v) background information etc. Each candidate word (a word having similar aspect ratio and topological feature to the query word) of the document is also coded accordingly. Then, an inexact string matching technique is used to measure the similarity between the primitive codes generated from the query word image and each candidate word of the document with which the query image is to be searched. Based on the similarity score, we retrieve the document where the query image is found. Experimental results on Bangla, Devnagari and Gurumukhi scripts document image databases confirm the feasibility and efficiency of our proposed approach.

关键词： Shape Encoding Image coding Image segmentation Feature extraction pattern recognition computer vision

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Bangla and english city name recognition for Indian postal automation

Bangla and english city name recognition for Indian postal a...

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International Conference on pattern Recognition

作者： Pal, Umapada Roy, Ramit Kumar Kimura, Fumitaka Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-108 India St. Xavier's College 30 Park Street Kolkata-16 India Graduate School of Engg. Mie University 1577 Kurimamachiya-cho Tsu 514-8507 Japan

ISBN: (纸本)9780769541099

Because of multi-lingual behavior destination address block of a postal document of an Indian state may be written in two or more scripts. From a statistical analysis of Indian postal document we noted that about 22.04% of Indian postal documents are written in two scripts. Because of inter-mixing of these scripts in postal address writings, it is very difficult to identify the script by which a city name is written. To avoid such identification difficulties, in this paper we proposed a lexicon-driven bi-lingual (English and Bangla) city name recognition scheme for Indian postal automation. We obtained 93.19% accuracy when tested on 11875 city name samples. © 2010 IEEE.

关键词： Automation

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MagiWrite: Towards touchless digit entry using 3D space around mobile devices

MagiWrite: Towards touchless digit entry using 3D space arou...

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12th International Conference on Human-computer Interaction with Mobile Devices and Services, Mobile HCI2010

作者： Ketabdar, Hamed Roshandel, Mehran Yüksel, Kamer Ali Quality and Usability Lab. Deutsche Telekom Laboratories TU Berlin Ernst-Reuter-Platz 7 10587 Berlin Germany Deutsche Telekom Laboratories Ernst-Reuter-Platz 7 10587 Berlin Germany Computer Vision and Pattern Analysis Lab. Sabanci University Istanbul Turkey

ISBN: (纸本)9781605588353

In this work, we present a new approach for text (mainly digit) entry based on digit shaped gestures created in 3D space around a mobile device. Some new mobile devices such as Apple iPhone 3GS and Google Android are equipped with magnetic (compass) sensor. The main idea is to influence the magnetic sensor using a magnet taken in hand. The user draws (writes) digits in the 3D space around the device using the magnet taken in hand. Movement of the magnet changes temporal pattern of magnetic field around the device which is sensed and registered by the magnetic (compass) sensor. The registered pattern is then compared against already recorded templates for different digits. Such a text (digit) entry approach can be especially useful for small mobile devices in which it is hard to operate small buttons or touch screen. Using our technique, the text entry space extends beyond physical boundaries of the device. A demonstrator for this approach is implemented on Apple iPhone 3GS platform. It demonstrates registering a few templates for different digits, and recognizing digits written in the space around the device.

关键词： Magnets

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A Bag-of-Pages Approach to Unordered Multi-page Document Classification

A Bag-of-Pages Approach to Unordered Multi-page Document Cla...

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International Conference on pattern Recognition

作者： Albert Gordo Florent Perronnin Computer Vision Center Universitat Autònoma Barcelona Spain Xerox Research Centre Europe Textual and Visual Pattern Analysis (TVPA) France

ISBN: (纸本)9781424475421

We consider the problem of classifying documents containing multiple unordered pages. For this purpose, we propose a novel bag-of-pages document representation. To represent a document, one assigns every page to a prototype in a codebook of pages. This leads to a histogram representation which can then be fed to any discriminative classifier. We also consider several refinements over this initial approach. We show on two challenging datasets that the proposed approach significantly outperforms a baseline system.

关键词： Histograms Training Accuracy Feature extraction Visualization Kernel Hidden Markov models

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Mash up of Breaking News and Contextual Web Information: A Novel Service for Connected Television

Mash up of Breaking News and Contextual Web Information: A N...

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International Conference on computer Communications and Networks (ICCCN)

作者： T. Chattopadhyay Arpan Pal Utpal Garain Innovation Laboratory Tata Consultancy Services Limited Kolkata India Computer Vision and Pattern Recognition Unit Tata Consultancy Services Limited Kolkata India

The Connected TV can be described as an Internet enabled TV. In the current paper we have proposed a system for connected TV that mash up the information from internet and RSS feeds related to the breaking news aired over the TV. The proposed system initially localize the text regions from the streamed video in hybrid mode, then recognize them and spot the key words and finally fetch the related information from Internet. Our experimental results show that the localization of the text regions from the video can work with no misses but have some false positives which are taken care by data semantic analysis. The errors of the Optical Character recognition (OCR) module are taken care by using string comparing techniques like longest common subsequence matching and Leveinsthein distance while matching with the RSS feed or internet.

关键词： TV Internet Optical character recognition software Pixel Feeds Accuracy Noise

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Word-Wise Handwritten Persian and Roman Script Identification

Word-Wise Handwritten Persian and Roman Script Identificatio...

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International Workshop on Frontiers in Handwriting Recognition

作者： Kaushik Roy Alireza Alaei Umapada Pal Department of Computer Science West Bengal State University Kolkata India Department of Studies in Computer Science University of Mysore Mysore India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Most of the countries use bi-script documents. This is because every country uses its own national language and English as second/foreign language. Therefore, bi-lingual document with one language being the English and other being the national language is very common. Postal documents are a very good example of such bi-lingual/script document. This paper deals with word-wise handwritten script identification from bi-script documents written in Persian and Roman. In the proposed scheme, simple but fast computable set of 12 features based on fractal dimension, position of small component, topology etc. are used and a set of classifiers are employed for script identification experiments. We tested our scheme on a dataset of 5000 handwritten Persian and English words and 99.20% of correct script identification is obtained.

关键词： Fractals Support vector machines Kernel Polynomials Training Artificial neural networks Neurons

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Text Independent Writer Identification for Bengali Script

Text Independent Writer Identification for Bengali Script

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International Conference on pattern Recognition

作者： Sukalpa Chanda Katrin Franke Umapada Pal Tetsushi Wakabayashi Department of Computer Science and Media Technology Gjovik University College Norway Computer Vision and Pattern Recognition Unit Indian Statistical Institute India Graduate School of Engineering Mie University Japan

ISBN: (纸本)9781424475421

Automatic identification of an individual based on his/her handwriting characteristics is an important forensic tool. In a computational forensic scenario, presence of huge amount of text/information in a questioned document cannot be always ensured. Also, compromising in terms of systems reliability under such situation is not desirable. We here propose a system to encounter such adverse situation in the context of Bengali script. Experiments with discrete directional feature and gradient feature are reported here, along with Support Vector Machine (SVM) as classifier. We got promising results of 95.19% writer identification accuracy at first top choice and 99.03% when considering first three top choices.

关键词： Accuracy Support vector machines Training Handwriting recognition Forensics Text analysis

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Script Identification – A Han and Roman Script Perspective

Script Identification – A Han and Roman Script Perspective

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International Conference on pattern Recognition

作者： Sukalpa Chanda Umapada Pal Katrin Franke Fumitaka Kimura Department of Computer Science and Media Technology Gjovik University College Norway Computer Vision and Pattern Recognition Unit Indian Statistical Institute India Graduate School of Engineering Mie University Japan

All Han-based scripts (Chinese, Japanese, and Korean) possess similar visual characteristics. Hence system development for identification of Chinese, Japanese and Korean scripts from a single document page is quite challenging. It is noted that a Han-based document page might also have Roman script in them. A multi-script OCR system dealing with Chinese, Japanese, Korean, and Roman scripts, demands identification of scripts before execution of respective OCR modules. We propose a system to address this problem using directional features along with a Gaussian Kernel-based Support Vector Machine. We got promising results of 98.39% script identification accuracy at character level and 99.85% at block level, when no rejection was considered.

关键词： Accuracy Support vector machines Training Kernel Feature extraction Image segmentation Optical character recognition software

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