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检索条件"机构=Computer Vision and Pattern"

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Lexicon reduction technique for Bangla handwritten word recognition

Lexicon reduction technique for Bangla handwritten word reco...

引用

10th IAPR International Workshop on Document Analysis Systems, DAS 2012

作者： Bhowmik, Tapan Kumar Roy, Utpal Parui, Swapan K. Faculty of Mathematics and Natural Sciences University of Groningen Netherlands Department of Computer and System Sciences Visva Bharati Santiniketan India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9780769546612

In this paper we introduce a stroke based lexicon reduction technique in order to reduce the search space for recognition of handwritten words. The principle of this technique involves mainly two aspects of a word image to constitute a feature vector: one is word-length and the other is shape of the word. The length of the word image is represented by the number of specific vertical strokes present in the word image and, on the other hand, the shape of a word image is realized with the combination of both horizontal and vertical strokes. The experiment has been carried out with a database of 35,700 off-line handwritten Bangla word images. Though our proposed lexicon reduction technique is developed for recognition of Bangla handwritten words, its generalization property can easily be exploited for recognition of handwriting in other scripts also. © 2012 IEEE.

关键词： Character recognition

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A new method for arbitrarily-oriented text detection in video

A new method for arbitrarily-oriented text detection in vide...

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10th IAPR International Workshop on Document Analysis Systems, DAS 2012

作者： Sharma, Nabin Shivakumara, Palaiahnakote Pal, Umapada Blumenstein, Michael Tan, Chew Lim Griffith University QLD Australia School of Computing National University of Singapore Singapore Singapore Computer Vision and Pattern Recognition Unit Indian Statistical Unit Kolkata India

ISBN: (纸本)9780769546612

Text detection in video frames plays a vital role in enhancing the performance of information extraction systems because the text in video frames helps in indexing and retrieving video efficiently and accurately. This paper presents a new method for arbitrarily-oriented text detection in video, based on dominant text pixel selection, text representatives and region growing. The method uses gradient pixel direction and magnitude corresponding to Sobel edge pixels of the input frame to obtain dominant text pixels. Edge components in the Sobel edge map corresponding to dominant text pixels are then extracted and we call them text representatives. We eliminate broken segments of each text representatives to get candidate text representatives. Then the perimeter of candidate text representatives grows along the text direction in the Sobel edge map to group the neighboring text components which we call word patches. The word patches are used for finding the direction of text lines and then the word patches are expanded in the same direction in the Sobel edge map to group the neighboring word patches and to restore missing text information. This results in extraction of arbitrarily-oriented text from the video frame. To evaluate the method, we considered arbitrarily-oriented data, non-horizontal data, horizontal data, Hua's data and ICDAR-2003 competition data (Camera images). The experimental results show that the proposed method outperforms the existing method in terms of recall and f-measure. © 2012 IEEE.

关键词： Pixels

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Off-line Bangla signature verification

Off-line Bangla signature verification

引用

10th IAPR International Workshop on Document Analysis Systems, DAS 2012

作者： Pal, Srikanta Nguyen, Vu Blumenstein, Michael Pal, Umapada School of Information and Communication Technology Griffith University Gold Coast QLD Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-700108 India

ISBN: (纸本)9780769546612

In the field of information security, biometric systems play an important role. Within biometrics, automatic signature identification and verification has been a strong research area because of the social and legal acceptance and extensive use of the written signature as an individual authentication. Signature verification is a process in which the questioned signature is examined in detail in order to determine whether it belongs to the claimed person or not. Despite substantial research in the field of signature verification involving Western signatures, very few works have been dedicated to non-Western signatures such as Chinese, Japanese, Arabic, or Persian etc. In this paper, the performance of an off-line signature verification system involving Bangla signatures, whose style is distinct from Western scripts, was investigated. The Gaussian Grid feature extraction technique was employed for feature extraction and Support Vector Machines (SVMs) were considered for classification. The Bangla signature database employed in the experiments consisted of 3000 forgeries and 2400 genuine signatures. An encouraging accuracy of 90.4% was obtained from the experiments. © 2012 IEEE.

关键词： Biometrics

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A probabilistic framework for logo detection and localization in natural scene images

A probabilistic framework for logo detection and localizatio...

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International Conference on pattern Recognition

作者： Ankush Roy Utpal Garain Computer Vision and Pattern Recognition Unit Indian Statistical Institute India

ISBN: (纸本)9781467322164

This paper presents a probabilistic approach for logo detection and localization in natural scene images. Two probability distributions are computed, one considering the features extracted from the key points located inside a region and the second refers to shape geometry defined by the key points. The barycentric co-ordinates are considered to define the shape statistics. The performance of the proposed approach has been reported on two publicly available datasets: BelgaLogos and Flickr Logos27. It is shown that statistically significant improvement is achieved over a recently proposed method.

关键词： Feature extraction Shape Geometry Accuracy Probabilistic logic Databases Visualization

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Visual place recognition for multi-robots maps merging

Visual place recognition for multi-robots maps merging

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IEEE International Workshop on Safety, Security, and Rescue Robotics (SSRR)

作者： Zhao Li Syed Riaz un Nabi Jafri Ryad Chellali Pattern Analysis & Computer Vision Istituto Italiano di Tecnologia Universita degli Studi di Genova Italy Pattern Analysis & Computer Vision Istituto Italiano di Tecnologia Italy

This paper presents a new approach allowing to a group of robots team to merge their individual maps without any a priori knowledge about their relative positions. While moving, each robot acquires laser data and a video stream. The first data are used to create individual maps (SLAM), while images sequences are used to derive invariant visual descriptions of the visited places. The later are then exchanged between robots to determine a probability of being close to each other and sharing a common place in order to initiate a map merging process. In such a way, ambiguous situations that usually occur when a single sensor is used are reduced. We present the solution we developed in order to extract a compact visual description that remains constant regardless to the actual pose of the robots. Two or more robots having such description can verify if they are or not present at the same place, before merging their respective individual maps. This scheme, e.g. the fusion of laser-range data and visual information enhances and accelerates the construction of the global map and consequently disambiguate individual maps. The validation of the approach has been performed on various indoor environments mainly, office-like spaces and houses.

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Anaphora Resolution in Bangla Using Global Discourse Knowledge

Anaphora Resolution in Bangla Using Global Discourse Knowled...

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International Conference on Asian Language Processing (IALP)

作者： Apurbalal Senapati Utpal Garain Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India

This paper presents a pronominal anaphora resolution (PAR) approach that makes use of the global discourse knowledge along with other traditional features. So far the features used in finding the referent of an anaphoric pronoun are computed locally. Normally the sentence containing the anaphor and a few sentences immediately before form the local context. In this process, the knowledge base gets updated as more and more of the discourse is processed. Keeping this approach as the core, the present paper explores use of some prior knowledge after examining the entire discourse (whole article). Addition of this processing step improves the PAR's efficiency. This improvement is demonstrated using ICON 2011 Bangla dataset.

关键词： Pragmatics Natural language processing Organizations Communities computer vision pattern recognition Roads

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A System for Handwritten and Machine-Printed Text Separation in Bangla Document Images

A System for Handwritten and Machine-Printed Text Separation...

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International Workshop on Frontiers in Handwriting Recognition

作者： Purnendu Banerjee B.B. Chaudhuri Indian Statistical Institute Computer Vision and Pattern Recognition Unit Kolkata India

In this paper, we describe an approach to distinguish between hand-written text and machine-printed text from annotated machine-printed Bangla Documents images. In applications involving OCR, distinction of machine-printed and hand-written characters is important, so that they can be sent to separate recognition engines. Identification of hand-written parts is useful in deleting those parts and cleaning the document image as well. In this paper a classification system is presented which takes a connected component in the document image and assigns them to two classes namely "machine-printed" and for "hand-written" classes, respectively. The proposed system contains a preprocessing step, which smoothes the object border and finds the Connected Component. Bangla script specific features are extracted from that Connected Component image, and a standard classifier based on SVM generates the final response. Experimental results on a data set show that the proposed approach achieves an overall accuracy of 96.49%.

关键词： Support vector machines Feature extraction Handwriting recognition Accuracy Text recognition Training

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Expressive Synthetic Voices: Considerations for Human Robot Interaction

Expressive Synthetic Voices: Considerations for Human Robot ...

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IEEE International Symposium on Robot and Human Interactive Communication

作者： S. Hennig R. Chellali Pattern Analysis & Computer Vision group at the Istituto Italiano di Technologia in affiliation with Universita degli Studi di Genova Pattern Analysis & Computer Vision group at the Istituto Italiano di Technologia

ISBN: (纸本)9781467346047

As speech synthesis technology develops more advanced paralinguistic capabilities, open questions emerge regarding how humans perceive the use of such vocal capabilities by robots. Perceptions of spoken interaction are complex and influenced by multiple factors including the linguistic content of a message, social context, perceived intelligence of the agent, and form factor of its embodiment. This paper shares results from a study that controlled for the above factors in order to investigate the effect on human listeners of a male synthetic voice with an expressive range. Participants were randomly assigned to three conditions, counterbalancing for gender and language background, in which how paralinguistic cues were applied was varied. As the voice became more expressive and appropriate for the context, observers were more likely to describe the communication as effective, but were less likely to refer to the unseen agent as a person. Possible effects of the listener gender and cultural-linguistic background are examined. Implications for future methodologies in this field are discussed.

关键词： Human machine interaction Voice Speech synthesis Listeners Gender Agents Intelligence SYNTHETICS Human

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Multi-view Photometric Stereo Using Semi-isometric Mappings

Multi-view Photometric Stereo Using Semi-isometric Mappings

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International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)

作者： Reza Sabzevari Alessio Del Bue Vittorio Murino Pattern Analysis and Computer Vision (PAVIS) Istituto Italiano di Tecnologia Genoa Italy

Classical uncalibrated Photometric Stereo approaches are mostly constrained to the static view assumption that enforces the camera to be fixed in front of an object illuminated by different light sources. Attempts to extend PS to multi-views has delivered methods that can only be robust to images taken with short camera baselines. In this paper, we present a new uncalibrated Multi-View Photometric Stereo (MVPS) method that can obtain a dense 3D reconstruction from views subject to strong baseline variations and extreme changes in illumination conditions. This approach is intrinsically photo geometric obtaining robust results using a combination of multi-view geometry and photometry. At the core of the algorithm, there is an efficient planar embedding and local image pixel registration among views that renders the problem tractable and computationally solvable. In the experiments, the results are evaluated and compared with the existing methods as well as the ground truth and shows the method is able to deal with the most complex objects and lighting conditions.

关键词： Lighting Transmission line matrix methods Shape Cameras Three dimensional displays Surface reconstruction Image reconstruction

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Low-level multimodal integration on Riemannian manifolds for automatic pedestrian detection

Low-level multimodal integration on Riemannian manifolds for...

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International Conference on Information Fusion

作者： Marco San-Biagio Marco Crocco Marco Cristani Samuele Martelli Vittorio Murino Pattern Analysis & Computer Vision (PAVIS) Istituto Italiano di Tecnologia (lIT) Genova Italy

In computer vision, automated pedestrian detection is surely one of the hottest topics, with important applications in surveillance and security. To this end, information integration from different imaging modalities, such as thermal infrared and visible spectrum, can significantly improve the detection rate with respect to monomodal strategies. A common scheme consists of extracting two sets of features, from thermal and visible images of the same scene respectively, and stacking them together into a single feature set, ignoring possible and meaningful inter-media dependencies. Here we propose a fusion scheme which acts at the feature-level, taking standard pixel characteristics (such as first/second order spatial derivatives or Local Binary pattern) and designing a composite descriptor that, at the same time, encodes the information coming from the separate modalities, as well as the cross-modal mutual relationships in the form of covariances. The descriptor, which lies on a Riemannian manifold, is projected onto a Euclidean tangent space and then fed into a Support Vector Machine classifier. Experiments performed on the OTCBVS dataset [1], and validated statistically, demonstrate that our method outperforms significantly the single modality policies as well as different fusion schemes at the pixel, feature and decision level.

关键词： Feature extraction Covariance matrix Imaging Vectors Standards Training Support vector machines

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