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International Conference on pattern recognition

作者： Maria C. Vill Robert Sablatnig Pattern Recognition and Image Processing Group Institute of Computer Aided Automation University of Technology Vienna Vienna Austria

ISBN: (纸本)9781424421749

This paper proposes a drawing tool recognition method based on features calculated from the shape of stroke endings. The application for this method is to help art historians to identify the drawing tool used for a drawing. Since the style of a drawing depends on the drawing tool used, drawing tool recognition is an important step toward a style analysis. A dominant feature of a drawn stroke is its ending. Several features regarding curvature, proportions etc. are calculated out of the shape of the endings. These features are then used to classify stroke endings with a SVM classifier.

关键词： Skeleton Shape pattern recognition Art Painting image segmentation Gray-scale Joining processes image analysis pattern analysis

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MULTISPECTRAL IMAGING FOR ANALYZING ANCIENT MANUSCRIPTS

MULTISPECTRAL IMAGING FOR ANALYZING ANCIENT MANUSCRIPTS

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European signal processing conference

作者： Martin Lettner Robert Sablatnig Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Vienna University of Technology 1040 Vienna Austria

ISBN: (纸本)9781617388767

In this paper we propose a method for segmenting characters in multispectral images of ancient documents. Due to the low quality of the document images the main idea of our 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. The whole process is parameter free since we calculate the stroke properties and the Gaussian parameters for the imaging model automatically. The study shows the effectiveness of using multispectral data for a computer aided analysis of ancient text documents. We compare the results of the proposed segmentation method to traditional methods based on color images as well as gray level images.

关键词： MULTISPECTRAL Computer aided analysis grayscale images Imaging Spatial Dependency image information color image field simulation

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Fuzzy headlight intensity controller using wireless sensor network

Fuzzy headlight intensity controller using wireless sensor n...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Victor Nutt Shubhalaxmi Kher Mehul Raval Electrical Engineering Arkansas State University Jonesboro USA Pattern Recognition and Image Processing Group DAIICT Gandhinagar India

ISBN: (纸本)9781479900213

This paper addresses the issue of headlight intensity to alleviate glare and blinding during night for drivers. Many factors are considered when analyzing automobile transportation in order to increase safety. One of the most prominent factors for night-time travel is temporary blindness due to elevated headlight intensity. This is particularly prominent on single lane roads. While headlight intensity provides better visual acuity, it inversely affects oncoming traffic. This problem is compounded when both drivers are using a higher headlight intensity setting. Also, higher speed due to decreased traffic levels at night increases the severity of accidents. In order to eliminate accidents due to temporary driver blindness, a fuzzy controller is designed based on the data captured using a wireless sensor network (WSN). Low latency allows quicker headlight intensity adjustment to minimize temporary blindness. Multiple attributes are taken into consideration for controller design. The results show that controller output is nearly instantaneous and generates control signal continuously.

关键词： Vehicles Roads Meteorology Wireless sensor networks Fuzzy logic Sensors

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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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Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance

作者： J. Aguilera H. Wildenauer M. Kampel M. Borg D. Thirde J. Ferryman Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria Computational Vision Group University of Reading Reading UK

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 aircrafts 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.

关键词： Motion segmentation Computer vision Aircraft Surveillance Robustness Statistical analysis Algorithm design and analysis Ground support Land vehicles Road vehicles

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Visual Odometry Drift Reduction Based on LiDAR Point Clouds Alignment

Visual Odometry Drift Reduction Based on LiDAR Point Clouds ...

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IEEE International Conference on Intelligent Computer Communication and processing (ICCP)

作者： Cătălin-Cosmin Golban Corvin-Petruţ Cobârzan Sergiu Nedevschi Technical University of Cluj-Napoca Romania Image Processing and Pattern Recognition Group Technical University of Cluj-Napoca Romania

ISBN: (纸本)9781665409773

Visual and LiDAR based odometry methods are key enablers for autonomous robots sub-problems such as mapping and localization or temporal aggregation and fusion of sensor data. When it comes to trajectory reconstruction the errors of independent local estimations accumulate over time, resulting in overall drifts from the real trajectory. This paper proposes a method for reducing the global drift by correcting the video-based frame-to-frame trajectory estimation at selected points in time based on the alignment of past and current LiDAR 3D measurements. The main strength of the proposed method is the formulation of the problem as a system of linear equations, which is an adequate numerical approximation as the corrective component is small enough. In this way we eliminate the need to deploy expensive non-linear optimization methods for calculating the correction transform.

关键词： Point cloud compression Visualization Laser radar Three-dimensional displays Estimation Transforms Robot sensing systems

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A new approach to finite wordlength coefficient fir digital filter design using the branch and bound technique 10

A new approach to finite wordlength coefficient fir digital ...

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2000 10th European Signal processing Conference, EUSIPCO 2000

作者： Belbachir, A.N. Boulerial, B. Belbachir, M.F. Signal and System Laboratory Electronic Institute U.S.T.O. B.P. 1505 El Mnouer Oran Algeria Vienna University of Technology Pattern Recognition and Image Processing Group Favritenstr. 9/1832 ViennaA-1040 Austria

ISBN: (纸本)9789521504433

It has been shown that the branch and bound technique is effective for the design of finite wordlength optimal digital filters. This technique is however expensive in computing time. In this paper, we present a robust branch and bound branching strategy named Sequential and Progressive Search, improving the design of filters on a large wordlength processor in a reasonable computing cost. The details of the algorithm and many examples are given and compared to the other methods. © 2000 EUSIPCO.

关键词： Digital filters

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Object-detection with a varying number of eigenspace projections

Object-detection with a varying number of eigenspace project...

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14th International Conference on pattern recognition, ICPR 1998

作者： Reiter, Michael Matas, Jiri Pattern Recognition and Image Processing Group Institute for Automation Vienna University of Technology A-1040 Vienna Austria CVSSP School of EE IT and Mathematics University of Surrey Guildford Surrey GU2 5XH United Kingdom

ISBN: (纸本)0818685123

We present a method allowing a significant speed-up of the eigen-detection method (detection based on principle component analysis). We derive a formula for an upper bound on the class-conditional probability (or equivalently a lower bound on the Mahalanobis distance) on which detection is based. Often, the lower bound of Mahalanobis distance (MD) reaches a preset threshold after computation of only a few eigen-projections. In this case the computation of MD can be immediately terminated. Regardless of the precise value of MD, the detection hypothesis (object from class Ω is detected) can be rejected. While provably obtaining results identical to the standard technique, we achieved a two- to three-fold speed-up in face detection experiments on images from the CMU database. © 1998 IEEE.

关键词： Face recognition

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Estimating the next sensor position based on surface characteristics

Estimating the next sensor position based on surface charact...

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International Conference on pattern recognition

作者： C. Liska R. Sablatnig Austrian Research Centre Seibersdorf Vienna Austria Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria

ISBN: (纸本)0769507506

In order to reconstruct the viewable surface of an object completely, multiple views of the same object have to be used and integrated into a common coordinate system. One of the major problems of the 3D surface reconstruction using a turntable, is the varying resolution in the direction to the camera, due to the varying distance of object points to the rotational axis of the turntable. To guarantee a uniform object resolution, we calculate the next angle dynamically, depending on the entropy of the surface part actually acquired. To minimize the loss of information and to guarantee a uniform surface resolution, we derive a relation between the entropy and the next viewing angle, based on the profile sections acquired in the last two steps of the acquisition.

关键词： Sensor phenomena and characterization Surface reconstruction image reconstruction Cameras Entropy Position measurement Shape measurement Java pattern recognition image processing

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Hierarchical top down enhancement of robust PCA 9th

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Joint IAPR 9th International Workshop on Structural and Syntactic pattern recognition, SSPR 2002 and 4th International Workshop on Statistical Techniques in pattern recognition, SPR 2002

作者： Langs, Georg Bischof, Horst Kropatsch, Walter G. Pattern Recognition and Image Processing Group 183/2 Institute for Computer Aided Automation Vienna University of Technology Favoritenstr. 9 ViennaA-1040 Austria Institute for Computer Graphics and Vision TU Graz Inffeldgasse 16 2.OG GrazA-8010 Austria

ISBN: (纸本)3540440119

In this paper we deal with performance improvement of robust PCA algorithms by replacing regular subsampling of images by an irregular image pyramid adapted to the expected image content. The irregular pyramid is a structure built based on knowledge gained from the training set of images. It represents different regions of the image with different level of detail, depending on their importance for reconstruction. This strategy enables us to improve reconstruction results and therefore the recognition significantly. The training algorithm works on the data necessary to perform robust PCA and therefore requires no additional input. © Springer-Verlag Berlin Heidelberg 2002.

关键词： image enhancement

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Automated segmentation of archaeological profiles for classification

Proceedings - International Conference on Pattern Recognitio...

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Proceedings - International Conference on pattern recognition 2002年第1期16卷 57-60页

作者： Kampel, Martin Sablatnig, Robert Vienna University of Technology Institute of Computer Aided Automation Pattern Recognition and Image Processing Group Favoritenstr.9/183-2 A-1040 Vienna Austria

Classification and reconstruction of archaeological fragments is based on the profile, which is the cross-section of the fragment in the direction of the rotational axis of symmetry. In order to segment the profile into primitives like rim, wall, and base, rules based on expert knowledge are created. The input data for the estimation of the profile is a set of points produced by the acquisition system. A function fitting this set is constructed and later on processed to find the characteristic points necessary to classify the original fragment. The one we propose is based on B-splines or bell-shaped splines. © 2002 IEEE.

关键词： image segmentation

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