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Pedestrian Detection in Infrared images Using HOG,LBP,Gradient Magnitude and Intensity Feature Channels

Pedestrian Detection in Infrared Images Using HOG,LBP,Gradie...

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17th International IEEE Conference on Intelligent Transportation Systems & The Asia-Pacific Council on Systems Engineering Conference 2014

作者： Raluca Brehar Sergiu Nedevschi the Image Processing and Pattern Recognition Group Computer Science DepartmentTechnical University of Cluj-Napoca

Recent work in monocular pedestrian detection is trying to improve the execution time while keeping the accuracy as high as possible.A popular and successful approach for monocular intensity pedestrian detection is based on the approximation（instead of computation） of image features for multiple scales based on the features computed on set of predefined *** port this idea to the infrared *** contributions reside in the combination of four channel features,namely infrared,histogram of gradient orientations,normalized gradient magnitude and local binary patterns with the objective of detecting pedestrians for night vision applications dealing with far infrared *** scale feature computation is done by feature *** contribution is the study of different formulations for Local Binary patterns like uniform patterns and rotation invariant patterns and their effect on detection *** detection speed is also boosted by the aid of a fast morphological based region of interest *** vary the number of approximated scales per octave and study the impact on execution time and accuracy.A reasonable result hits a speed of 18 fps with a log average miss rate of 39%.

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Robust Parametric and Semi-parametric Spot Fitting for Spot Array images 8

Robust Parametric and Semi-parametric Spot Fitting for Spot ...

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8th International Conference on Intelligent Systems for Molecular Biology, ISMB 2000

作者： Brändle, Norbert Chen, Horng-Yang Bischof, Horst Lapp, Hilmar Vienna University of Technology Pattern Recognition and Image Processing Group Treitlstr. 3/1832 ViennaA-1040 Austria Novartis Research Institute Vienna Genetics Brunner Str. 59 ViennaA-1230 Austria

ISBN: (纸本)1577351150

In this paper we address the problem of reliably fitting parametric and semi-parametric models to spots in high density spot array images obtained in gene expression experiments. The goal is to measure the amount of label bound to an array element. A lot of spots can be modelled accurately by a Gaussian shape. In order to deal with highly overlapping spots we use robust M-estimators. When the parametric method fails (which can be detected automatically) we use a novel, robust semi-parametric method which can handle spots of different shapes accurately. The introduced techniques are evaluated experimentally. Copyright © 2000, American Association for Artificial Intelligence (***). All rights reserved.

关键词： Gene expression

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Word Channel Based Multiscale Pedestrian Detection Without image Resizing and Using Only One Classifier

Word Channel Based Multiscale Pedestrian Detection Without I...

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IEEE Conference on Computer Vision and pattern recognition

作者： Arthur Daniel Costea Sergiu Nedevschi Image Processing and Pattern Recognition Group Computer Science Department Technical University of Cluj-Napoca

ISBN: (纸本)9781479951192

Most pedestrian detection approaches that achieve high accuracy and precision rate and that can be used for real-time applications are based on histograms of gradient orientations. Usually multiscale detection is attained by resizing the image several times and by recomputing the image features or using multiple classifiers for different scales. In this paper we present a pedestrian detection approach that uses the same classifier for all pedestrian scales based on image features computed for a single scale. We go beyond the low level pixel-wise gradient orientation bins and use higher level visual words organized into Word Channels. Boosting is used to learn classification features from the integral Word Channels. The proposed approach is evaluated on multiple datasets and achieves outstanding results on the INRIA and Caltech-USA benchmarks. By using a GPU implementation we achieve a classification rate of over 10 million bounding boxes per second and a 16 FPS rate for multiscale detection in a 640×480 image.

关键词： Visualization Boosting Training Feature extraction Graphics processing units Semantics image color analysis

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Hierarchical classification of paintings using face- and brush stroke models

Hierarchical classification of paintings using face- and bru...

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International Conference on pattern recognition

作者： R. Sablatnig P. Kammerer E. Zolda Institute of Automation Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria

It is often difficult to attribute works of art to a certain artist. In the case of paintings, radiological methods like X-ray and infra-red diagnosis, digital radiography, computer-tomography, etc. and color analyzes are employed to authenticate works of art. But all these methods do not relate certain characteristics of an art work to a specific artist-the artist's personal style. In order to study this personal style, we examine the "structural signature" based on brush strokes in particular in portrait miniatures. A computer-aided classification and recognition system for portrait miniatures is developed, which enables a semi-automatic classification based on brush strokes. A hierarchically structured classification scheme is introduced which separates the classification into three different levels of information: color, shape of region, and structure of brush strokes.

关键词： Painting Art Humans Face Automation pattern recognition image processing Postal services Trademarks Rhythm

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Evaluation of motion segmentation quality for aircraft activity surveillance

Evaluation of motion segmentation quality for aircraft activ...

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2nd Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, VS-PETS

作者： Aguilera, Josep Wildenauer, Horst Kampel, Martin Borg, Mark Thirde, David Ferryman, James Pattern Recognition and Image Processing Group Vienna University of Technology Favoritenstr.9 183-2 A-1040 Vienna Austria Computational Vision Group University of Reading Whiteknights Reading RG6 6AY United Kingdom

ISBN: (纸本)0780394240

Recent interest has been shown in performance evaluation of visual surveillance systems. The main purpose of performance evaluation on computer vision systems is the statistical testing and tuning in order to improve algorithm's reliability and robustness, In this paper we investigate the use of empirical discrepancy metrics for quantitative analysis of motion segmentation algorithms. We are concerned with the case of visual surveillance on an airport's apron, that is the area where aircraft s are parked and serviced by specialized ground support vehicles. Robust detection of individuals and vehicles is of major concern for the purpose of tracking objects and understanding the scene. In this paper, different discrepancy metrics for motion segmentation evaluation are illustrated and used to assess the performance of three motion segmentors on video sequences of an airport's apron. © 2005 IEEE.

关键词： image segmentation

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pattern recognition 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Walter G. Kropatsch Robert Sablatnig Allan Hanbury

ISBN: (数字)9783540319429

ISBN: (纸本)9783540287032

It is both an honor and a pleasure to hold the 27th Annual Meeting of the German Association for pattern recognition, DAGM 2005, at the Vienna U- versity of Technology, Austria, organized by the pattern recognition and image processing (PRIP) group. We received 122 contributions of which we were able to accept 29 as oral presentations and 31 as posters. Each paper received three reviews, upon which decisions were made based on correctness, presentation, technical depth, scienti?c signi?cance and originality. The selection as oral or poster presentation does not signify a quality grading but re?ects attractiveness to the audience which is also re?ected in the order of appearance of papers in these proceedings. The papers are printed in the same order as presented at the symposium and posters are integrated in the corresponding thematic session. In putting these proceedings together, many people played signi?cant roles which we would like to acknowledge. First of all our thanks go to the authors who contributed their work to the symposium. Second, we are grateful for the dedicated work of the 38 members of the Program Committee for their e?ort in evaluating the submitted papers and inprovidingthe necessarydecisionsupport information and the valuable feedback for the authors. Furthermore, the P- gram Committee awarded prizes for the best papers, and we want to sincerely thank the donors. We were honored to have the following three invited speakers at the conf- ence: – Jan P.

关键词： pattern recognition image processing and Computer Vision Artificial Intelligence Computer Graphics Algorithm Analysis and Problem Complexity

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Blind background subtraction in dental panoramic X-ray images: An application approach

Blind background subtraction in dental panoramic X-ray image...

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27th DAGM (German Association for pattern recognition) Symposium, DAGM 2005

作者： Goebel, Peter Michael Belbachir, Nabil Ahmed Truppe, Michael Vienna University of Technology Institute of Computer Aided Automation Pattern Recognition and Image Processing Group Austria Fh-campus Wien Technical Project- and Processmanagement Austria Karl Landsteiner Institute for Biotelematics Danube University Krems Austria

Dental Panoramic X-ray images are images having complex content, because several layers of tissue, bone, fat, etc. are superimposed. Non-uniform illumination, stemming from the X-ray source, gives extra modulation to the image, which causes spatially varying X-ray photon density. The interaction of the X-ray photons with the density of matter causes spatially coherent varying noise contribution. Many algorithms exist to compensate background effects, by pixel based or global methods. However, if the image is contaminated by a non-negligible amount of noise, that is usually non-Gaussian, the methods cannot approximate the background efficiently. In this paper, a dedicated approach for background subtraction is presented, which operates blind, that means the separation of a set of independent signals from a set of mixed signals, with at least, only little a priori information about the nature of the signals, using the A-Trous multiresolution transform to alleviate this problem. The new method estimates the background bias from a reference scan, which is taken without a patient. The background values are rescaled by a polynomial compensation factor, given by mean square error criteria, thus subtracting the background will not produce additional artifacts in the image. The energy of the background estimate is subtracted from the energy of the mixture. The method is capable to remove spatially varying noise also, allocating an appropriate spatially noise estimate. This approach has been tested on 50 images from a database of panoramic X-ray images, where the results are cross validated by medical experts. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Medical imaging

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Next view planning for a combination of passive and active acquisition techniques

Next view planning for a combination of passive and active a...

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

作者： R. Sablatnig S. Tosovic M. Kampel Pattern Recognition and Image Processing Group Institute for Computer Aided Automation University of Technology Vienna Austria

In order to create a complete three-dimensional model of an object based on its two-dimensional images, the images have to be acquired from different views. An increasing number of views generally improves the accuracy of the final 3D model but it also increases the time needed to build the model. The number of the possible views can theoretically be infinite. Therefore, it makes sense to try to reduce the number of views to a minimum while preserving a certain accuracy of the model, especially in applications for which the performance is an important issue. We show an approach to next view planning for a fusion of shape from Silhouette, as an example of a passive 3D reconstruction technique, and shape from structured light, as an example of an active 3D reconstruction technique in order to get 3D shape reconstruction with minimal different views. Results of the algorithm developed are presented for both synthetic and real input images.

关键词： image reconstruction Shape Sensor phenomena and characterization Sensor systems Computer vision pattern recognition image processing Automation Joining processes Out of order

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Spatial and Spectral Based Segmentation of Text in Multispectral images of Ancient Documents

Spatial and Spectral Based Segmentation of Text in Multispec...

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International Conference on Document Analysis and recognition

作者： Martin Lettner Robert Sablatnig Pattern Recognition and Image Processing Group Institute of Computer Aided Automation University of Technology Vienna Austria

ISBN: (纸本)9781424445004

In this paper we propose a character segmentation method for multispectral images of ancient documents. Due to the low quality of the images the main idea of this study is to combine the multispectral behavior and contextual spatial information. Therefore we utilize a Markov random field model using the spectral information of the images and stroke properties to include spatial dependencies of the characters. Since the stroke properties and the Gaussian parameters for the imaging model are evaluated automatically the proposed segmentation method requires no training phase. We compared the method to state of the art character segmentation methods and demonstrate the effectiveness of combining spectral and spatial features for the segmentation of characters in multispectral images.

关键词： image segmentation Multispectral imaging image analysis Color Independent component analysis Text analysis Character recognition pattern recognition Markov random fields pattern analysis

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Distinguishing 3D-Topological Configurations of Two Tori

Distinguishing 3D-Topological Configurations of Two Tori

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International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)

作者： Adrian Ion Thomas Illetschko Yll Haxhimusa Walter G. Kropatsch Pattern Recognition and Image Processing Group Institute of Computer Aided Automation University of Technology Vienna Austria

Most of the existing work regarding topology preserving hierarchies is mainly preoccupied with 2D domains. But recently attention has turned to 3D, and more generally, nD representations. Even more than in 2D, the necessity for reducing these representations exists and motivates the research in hierarchical structures i.e. pyramids. Using representations that support any dimension, like e.g. the combinatorial map, n dimensional irregular pyramids can be built, thus obtaining reduced representations of the original data, while preserving the topology. This paper presents 3D combinatorial maps and the primitive operations needed to simplify such representations. Minimal configurations of the three primitive topological configurations, simplex, hole, and tunnel, and two possible configurations for two tori are presented. Experimental results and possible applications show the potential of the approach

关键词： Topology image edge detection Geology Solid modeling image segmentation Mechanical factors pattern recognition image processing Automation Shape

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