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检索条件"机构=Computer vision and Image processing lab"

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Classification of gothic and baroque architectural elements

Classification of gothic and baroque architectural elements

引用

2012 19th International Conference on Systems, Signals and image processing, IWSSIP 2012

作者： Shalunts, Gayane Haxhimusa, Yll Sablatnig, Robert Institute of Computer Aided Automation Computer Vision Lab. Vienna University of Technology Austria Institute of Computer Graphics and Algorithms Pattern Recognition and Image Processing Lab. Vienna University of Technology Austria

ISBN: (纸本)9783200023284

Architectural elements are the components and details of buildings. Their unique set, combination, design, construction technique form the architectural style of buildings. Building facade classification by architectural styles is viewed as a task of classifying separate architectural structural elements. In the scope of building facade architectural style classification the current paper targets the problem of classification of Gothic and Baroque architectural elements called tracery, pediment and balustrade. Since certain gradient directions dominate on the shape of each architectural element, discrimination between dominating gradients means classification of architectural elements and thus architectural styles. We use local features to describe gradient directions. Our approach is based on clustering and learning of local features and yields a high classification rate. © 2012 Institute of Telecommunica.

关键词： Classification (of information)

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Architectural style classification of building facade windows

Architectural style classification of building facade window...

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7th International Symposium on Visual Computing, ISVC 2011

作者： Shalunts, Gayane Haxhimusa, Yll Sablatnig, Robert Institute of Computer Aided Automation Computer Vision Lab. Vienna University of Technology Austria Institute of Computer Graphics and Algorithms Pattern Recongition and Image Processing Lab. Vienna University of Technology Austria

Building facade classification by architectural styles allows categorization of large databases of building images into semantic categories belonging to certain historic periods, regions and cultural influences. image databases sorted by architectural styles permit effective and fast image search for the purposes of content-based image retrieval, 3D reconstruction, 3D city-modeling, virtual tourism and indexing of cultural heritage buildings. Building facade classification is viewed as a task of classifying separate architectural structural elements, like windows, domes, towers, columns, etc, as every architectural style applies certain rules and characteristic forms for the design and construction of the structural parts mentioned. In the context of building facade architectural style classification the current paper objective is to classify the architectural style of facade windows. Typical windows belonging to Romanesque, Gothic and Renaissance/Baroque European main architectural periods are classified. The approach is based on clustering and learning of local features, applying intelligence that architects use to classify windows of the mentioned architectural styles in the training stage. © 2011 Springer-Verlag.

关键词： Semantics

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Interest point based tracking

Interest point based tracking

引用

2010 20th International Conference on Pattern Recognition, ICPR 2010

作者： Kloihofer, Werner Kampel, Martin Research and Development Image Processing Center Communication Systems GmbH Vienna Austria Computer Vision Lab. Vienna University of Technology Vienna Austria

ISBN: (纸本)9780769541099

This paper deals with a novel method for object tracking. In the first step interest points are detected and feature descriptors around them are calculated. Sets of known points are created, allowing tracking based on point matching. The set representation is updated online at every tracking step. Our method uses one-shot learning with the first frame, so no offline and no supervised learning is required. Following an object recognition based approach there is no need for a background model or motion model, allowing tracking of abrupt motion and with non-stationary cameras. We compare our method to MeanShift and Tracking via Online Boosting, showing the benefits of our approach. © 2010 IEEE.

关键词： Object detection

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An approach to large scale interactive retrieval of cultural heritage

An approach to large scale interactive retrieval of cultural...

引用

2014 Eurographics Workshop on Graphics and Cultural Heritage, GCH 2014

作者： Takami, Masato Bell, Peter Ommer, Bjrn Heidelberg Collaboratory for Image Processing IWR University of Heidelberg Germany Robert Bosch GmbH Corporate Research Computer Vision Research Lab Hildesheim Germany

ISBN: (纸本)9783905674637

Large scale digitization campaigns are simplifying the accessibility of a rapidly increasing number of images from cultural heritage. However, digitization alone is not sufficient to effectively open up these valuable resources. Retrieval and analysis within these datasets is currently mainly based on manual annotation and laborious preprocessing. This is not only a tedious task, which rapidly becomes infeasible due to the enormous data load. We also risk to be biased to only see what an annotator beforehand has focused on. Thus a lot of potential is being wasted. One of the most prevalent tasks is that of discovering similar objects in a dataset to find relations therein. The majority of existing systems for this task are detecting similar objects using visual feature keypoints. While having a low processing time, these methods are limited to detect only close duplicates due to their keypoint based representation. In this work we propose a search method which can detect similar objects even if they exhibit considerable variability. Our procedure learns models of the appearance of objects and trains a classifier to find related *** address a central problem of such learning-based methods, the need for appropriate negative and positive training samples. To avoid a highly complicated hard negative mining stage we propose a pooling procedure for gathering generic negatives. Moreover, a bootstrap approach is presented to aggregate positive training samples. Comparison of existing search methods in cultural heritage benchmark problems demonstrates that our approach yields significantly improved detection performance. Moreover, we show examples of searching across different types of datasets, e.g., drafts and photographs. © 2014 All rights reserved.

关键词： Benchmarking

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Recognition of hand punched Kannada Braille characters using knowledge based multi decision concept: Basic symbols

Recognition of hand punched Kannada Braille characters using...

引用

International Conference on Advances in Computing, ICAdC 2012

作者： Srinath, S. Ravi Kumar, C.N. Image Processing and Computer Vision Lab. Department of Computer Science and Engineering S.J. College of Engineering Mysore City Karnataka State 570 006 India

ISBN: (纸本)9788132207399

Technology has made the visually impaired life more comfortable. Access to textual information has become simple to the visually impaired community. Braille is widely used as communication tool for visually impaired people. The reading and writing communication for the visually impaired is available through the Braille language all over the world. Braille notations are available for most of the languages all over the world. Kannada is a south Indian language, which follows syllable writing method. People who work in association with visually impaired and can't understand Braille notation, require conversion of Braille document into a normal language representation. This paper presents an efficient algorithm for converting a Kannada Braille symbols into its equivalent normal version. Hand punched Kannada Braille document is used for the experimentation. The document image is segmented to extract Braille characters one at a time and compared with the knowledge base created to identify the equivalent normal version of it. Six different knowledge bases are created to reduce the search time complexity. © 2013 Springer.

关键词： Optical character recognition

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Statistically Robust Approach to Lens Distortion Calibration with Model Selection

Statistically Robust Approach to Lens Distortion Calibration...

引用

Conference on computer vision and Pattern Recognition Workshop, CVPRW 2003

作者： Taha El-Melegy, Moumen Farag, Aly A. Electrical Engineering Dept. Assiut University Assiut Egypt Computer Vision and Image Processing Lab. University of Louisville LouisvilleKY40292 United States

ISBN: (纸本)0769519008

This paper addresses the problem of calibrating camera lens distortion, which can be significant in medium to wide angle lenses. While almost all existing nonmetric distortion calibration methods need user involvement in one form or another,we present an approach to distortion calibration based on the robust the-least-median-of-squares (LMedS) estimator. Our approach is thus able to proceed in a ful ly-automatic manner while being less sensitive to erroneous input data such as image curves that are mistakenly considered as projections of 3D linear segments. Our approach uniquely uses fast, closed-form solutions to the distortion coefficients, which serve as an initial point for a non-linear optimization algorithm to straighten imaged lines. Moreover we propose a method for distortion model selection based on geometrical *** experiments to evaluate the performance of this approach on synthetic and real data are reported. © 2003 IEEE.

关键词： Least squares approximations

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A Simplified Skeleton Joints Based Approach For Human Action Recognition 7

A Simplified Skeleton Joints Based Approach For Human Action...

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7th IEEE International Conference on Signal and image processing Applications, ICSIPA 2021

作者： Malik, Najeeb Ur Rehman Abu Bakar, Syed A.R. Sheikh, Usman Ullah Computer Vision Video and Image Processing Research Lab School of Electrical Engineering Faculty of Engineering Universiti Teknologi Malaysia UTM Johor Bahru Campus Johor 81310 Malaysia

ISBN: (纸本)9781665435925

The growing technological development in the field of computer vision in general, and human action recognition (HAR), in particular, have attracted increasing number of researchers from various disciplines. Amid the variety of challenges in the field of human action recognition, one of the major issues is complex modelling which requires multiple parameters leading to troublesome training which further requires heavy configuration machines for real-time recognition. Therefore, there is a need to develop a simplified method that could result in reduced complexity, without compromising the performance accuracy. In order to address the mentioned issue, this paper proposes an approach that extracts the mean, variance and median from the skeleton joint locations and directly uses them in the classification process. The system used MCAD dataset for extracting 2D skeleton features with the help of OpenPose technique, which is suitable for the extraction of skeleton features from the 2D image instead of 3D image or using a depth sensor. Henceforth, we avoid using either the RGB images or the skeleton images in the recognition process. The method shows a promising performance with an accuracy of 73.8% when tested with MCAD dataset. © 2021 IEEE

关键词： image processing

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Learning Robust Models Using the Principle of Independent Causal Mechanisms 43rd

Learning Robust Models Using the Principle of Independent ...

引用

43rd DAGM German Conference on Pattern Recognition, DAGM GCPR 2021

作者： Müller, Jens Schmier, Robert Ardizzone, Lynton Rother, Carsten Köthe, Ullrich Heidelberg Collaboratory for Image Processing Heidelberg University Heidelberg Germany Computer Vision and Learning Lab Heidelberg University Heidelberg Germany Bosch Center for Artificial Intelligence Renningen Germany

ISBN: (纸本)9783030926588

Standard supervised learning breaks down under data distribution shift. However, the principle of independent causal mechanisms (ICM, [31]) can turn this weakness into an opportunity: one can take advantage of distribution shift between different environments during training in order to obtain more robust models. We propose a new gradient-based learning framework whose objective function is derived from the ICM principle. We show theoretically and experimentally that neural networks trained in this framework focus on relations remaining invariant across environments and ignore unstable ones. Moreover, we prove that the recovered stable relations correspond to the true causal mechanisms under certain conditions, turning domain generalization into a causal discovery problem. In both regression and classification, the resulting models generalize well to unseen scenarios where traditionally trained models fail. © 2021, Springer Nature Switzerland AG.

关键词： Learning systems

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Human object classification in daubechies complex wavelet domain 2nd

Human object classification in daubechies complex wavelet do...

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2nd International Conference on Context-Aware Systems and Applications, ICCASA 2013

作者： Khare, Manish Srivastava, Rajneesh Kumar Khare, Ashish Binh, Nguyen Thanh Dien, Tran Anh Image Processing and Computer Vision Lab Department of Electronics and Communication University of Allahabad Allahabad India Ho Chi Minh City University of Technology Ho Chi Minh Viet Nam

ISBN: (纸本)9783319059389

Human object classification is an important problem for smart video surveillance applications. In this paper we have proposed a method for human object classification, which classify the objects into two classes: human and non-human. The proposed method uses Daubechies complex wavelet transform coefficients as a feature of object. Daubechies complex wavelet transform is used due to its better edge representation and approximate shift-invariant property as compared to real valued wavelet transform. We have used Adaboost as a classifier for classification of objects. The proposed method has been tested on standard datasets like, INRIA dataset. Quantitative experimental evaluation results show that the proposed method is better than other state-of-the-art methods and gives better performance. © Springer International Publishing Switzerland 2014.

关键词： Adaptive boosting

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Multiple objects segmentation based on maximum-likelihood estimation and optimum entropy-distribution(MLE-OED)

Multiple objects segmentation based on maximum-likelihood es...

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16th International Conference on Pattern Recognition, ICPR 2002

作者： Jun, Xie Tsui, H.T. Deshen, Xia Image Processing and Computer Vision Lab Department of Electronic Engineering Chinese University of Hong Kong Hong Kong Pattern Recognition Lab Department of Computer Science Nanjing University of Sci.andTech. China

ISBN: (纸本)0769516963

A new method based on MLE-OED is proposed for unsupervised image segmentation of multiple objects which have fuzzy edges. It adjusts the parameters of a mixture of Gaussian distributions via minimizing a new loss function proposed to implement image segmentation based on the image's local spatial information and global intensity distribution properties . The loss function consists of two terms: a local content fitting term, which optimizes the entropy distribution, and a global statistical fitting term, which maximizes the likelihood of the parameters for the given data. The proposed segmentation method was validated by simulated and real examples Its performance in the experiments is better than those of two popular methods. © 2002 IEEE.

关键词： Maximum likelihood estimation

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