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IEEE International Conference on image processing

作者： C. Beleznai H. Ramoser B. Wachmann J. Birchbauer H. Bischof W. Kropatsch Advanced Computer Vision Austrian Research Centre Seibersdorf Vienna Austria Programm-und Systementwicklung Siemens AG Österreich Graz Austria Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria

Fingerprint recognition and verification are often based on local fingerprint features, usually ridge endings or terminations, also called minutiae. By exploiting the structural uniqueness of the image region around a minutia, the fingerprint recognition performance can be significantly enhanced. However, for most fingerprint images the number of minutia image regions (MIRs) becomes dramatically large, which imposes - especially for embedded systems - an enormous memory requirement. Therefore, we are investigating different algorithms for compression of minutia regions. The requirement for these algorithms is to achieve a high compression rate (about 20) with minimum loss in the matching performance of minutia image region matching. We investigate the matching performance for compression algorithms based on the principal component and the wavelet transformation. The matching results are presented in form of normalized ROC curves and interpreted in terms of compression rates and the MIR dimension.

关键词： Fingerprint recognition image coding Computer vision image recognition image processing image matching Embedded system Performance loss Biometrics Character recognition

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Mobile robot localization under varying illumination

Mobile robot localization under varying illumination

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16th International Conference on pattern recognition, ICPR 2002

作者： Jogan, Matjaž Leonardis, Aleš Wildenauer, Horst Bischof, Horst Faculty of Computer and Information Science University of Ljubljana Tržaška 25 Ljubljana1001 Slovenia Pattern Recognition and Image Processing Group Institute for Computer Aided Automation Vienna University of Technology Favoritenstrasse 9/1832 ViennaA-1040 Austria Institute for Computer Graphics and Vision Graz University of Technology Inffeldgasse 16 2. OG GrazA-8010 Austria

ISBN: (纸本)0769516963

Methods for mobile robot localization that use eigen spaces of panoramic snapshots of the environment are in general sensitive to changes in the illumination of the environment. Therefore, we propose an approach which achieves a reliable localization under severe illumination conditions. The method uses gradient filtering of the eigen space. After testing the approach on images obtained by a mobile robot, we show that it outperforms the standard eigen space-based recognition method. © 2002 IEEE.

关键词： Mobile robots

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Embedded Real-Time Ball Detection Unit for the YABIRO Biped Robot

Embedded Real-Time Ball Detection Unit for the YABIRO Biped ...

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Workshop on Intelligent Solutions in Embedded Systems

作者： Markus Bader Miguel Albero Robert Sablatnig Jose E. Simo Gines Benet Gregor Novak Francisco Blanes Institute of Computer Aided Automation Pattern Recognition and Image Processing Group University of Technology Vienna Austria Departamento de Informática de Sistemas y Computadores Universidad Politécnica de Valencia Spain

Estimation of objects in a 3D space is a fundamental problem in computer vision and robotics. This paper describes an algorithm and its implementation for a vision module as a sensor of a biped robot (YABIRO). The embedded vision sensor is able to estimate the position of objects like spheres in 3D space. Objects are defined with their size and color in a model. The vision sensor detects the positions or at least the directions to the objects and stores them in a history. The algorithm includes a new voting system for detected objects, based on how trustable the detection was, and a new edge filter to terminate edges on the circle border for the circle detection. The systems frame rate depends on the area of interest and lies between 5 Hz and 20 Hz. With a mechanical size of 36times32mm it is smaller than a matchbox

关键词： Object detection Robot sensing systems Robot vision systems Computer vision Space technology Detection algorithms Hardware Embedded computing image edge detection Cameras

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Virtual Vessel Reconstruction from a Fragment's Profile

Virtual Vessel Reconstruction from a Fragment's Profile

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4th International Symposium on Virtual Reality, Archaeology and Intelligent Cultural Heritage, VAST 2003

作者： Kampel, M. Melero, F.J. Vienna University of Technology Institute of Computer Aided Automation Pattern Recognition and Image Processing Group Favoritenstr. 9 183-2 ViennaA-1040 Austria Universidad de Granada E.T.S. Ingeniería Informática Dpt. Lenguajes y Sistemas Informáticos C/. Daniel Saucedo Aranda s/n GranadaE-18071 Spain

ISBN: (纸本)3905673088

Every archaeological excavation must deal with a vast number of ceramic fragments. The documentation, administration and scientific processing of these fragments represent a temporal, personnel, and financial problem. Up to now documentation and classification have been done manually which means a lot of routine work for archaeologists and a very inconsistent representation of the real object. First, there may be errors in the measuring process (diameter or height may be inaccurate). Second, the drawing of the fragment should be in a consistent style, which is not possible since a drawing of an object without interpreting it is very hard to do. We are developing a documentation system for archaeological fragments based on their profile, which is the cross-section of the fragment in the direction of the rotational axis of symmetry. Hence the position of a fragment (orientation) on a vessel is important, since it allows a good profile to be obtained. This paper presents two different approaches to the estimation of the orientation of archaeological fragments and the profile extraction. One method is based on a Hough inspired approach and the other is based on genetic algorithms and expert interaction. We compare the methods and show results with respect to robustness, applicability, and accuracy. © The Eurographics Association 2003.

关键词： Genetic algorithms

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Speed estimation for scene objects using stereo visual odometry methods

Speed estimation for scene objects using stereo visual odome...

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IEEE International Conference on Intelligent Computer Communication and processing

作者： Catalin Golban Sergiu Nedevschi Image Processing and Pattern Recognition Group Computer Science Department Technical University of Cluj-Napoca

ISBN: (纸本)9781479914920

This paper proposes a novel method to determine the speed of the surrounding vehicles in traffic scenarios. Relying on the video information obtained from a stereo camera mounted on a moving vehicle, we first determine the vehicle ego motion based on static scene features then we determine the relative motion between objects based on features situated on the moving objects. For robustness to false feature matches everything is plugged into a multi-RANSAC framework. The novelty of the method consist in the fact that the relative motion between the objects can be determined with the same algorithm that was previously used for ego motion estimation, the only difference consisting in the geometric constraints that are imposed to the subset of point features considered for inliers set detection and evaluation. Also, the proposed method does not rely on the fact that objects are detected previously and it does not detect the objects.

关键词： Visual odometry Obstacles speed Speed detection Ego motion Motion estimation Speed estimation

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A global method for reducing multidimensional size graphs

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2011年 6658 LNCS卷 1-11页

作者： Cerri, Andrea Frosini, Patrizio Kropatsch, Walter G. Landi, Claudia Vienna University of Technology Faculty of Informatics Pattern Recognition and Image Processing Group Austria Università di Bologna ARCES Dipartimento di Matematica Italy Università di Modena e Reggio Emilia Dipartimento di Scienze e Metodi dell'Ingegneria Italy

ISBN: (纸本)9783642208430

This paper introduces the concept of discrete multidimensional size function, a mathematical tool studying the so-called size graphs. These graphs constitutes an ingredient of Size Theory, a geometrical/topological approach to shape analysis and comparison. A global method for reducing size graphs is presented, together with a theorem stating that size graphs reduced in such a way preserve all the information in terms of multidimensional size functions. This approach can lead to simplify the effective computation of discrete multidimensional size functions, as shown by examples. © 2011 Springer-Verlag Berlin Heidelberg.

关键词： Graphic methods

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Research on the Strike Strategy of Quadcopter Unmanned Aerial Vehicles for Mobile Targets

Research on the Strike Strategy of Quadcopter Unmanned Aeria...

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WRC Symposium on Advanced Robotics and Automation (WRC SARA)

作者： Wencai Zhang Junjie Sun Yanying Li Shen Yan Ning Zhang Jiaqi Wang Zhihua Chen Mingran Pan Engineering Technicians of Norinco Group Liao Shen Industries Group CO.LTD Shenyang China Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition and MOE Key Lab of Nondestructive Testing Technology Nanchang Hangkong University Nanchang China

ISBN: (数字)9798331506100

ISBN: (纸本)9798331506117

This paper studies a strike path strategy for quadcopter drones targeting ground maneuvering targets. The strategy sets the strike path to two different strike speeds, which improves the stability and robustness of quadcopter drones while shortening strike time and increasing hit rates. Consider the attitude control of quadcopter unmanned aerial vehicles during motion, and verify the flight reliability of the mechanism through simulation experiments. Set different slope strike paths and obtain the optimal strike path through experiments, while proving the effectiveness of this strike strategy in engineering applications.

关键词： Attitude control Prototypes Autonomous aerial vehicles Stability analysis Robustness Robotics and automation Aircraft propulsion

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Single landmark based self-localization of mobile robots

Single landmark based self-localization of mobile robots

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Canadian Conference on Computer and Robot Vision, CRV

作者： A. Bais R. Sablatnig J. Gu Robotics Research Group Department of Electrical and Computer Engineering Dalhousie University Halifax Canada Institute of Computer Technology University of Technology Vienna Vienna Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation University of Technology Vienna Vienna Austria

In this paper we discuss landmark based absolute localization of tiny autonomous mobile robots in a known environment. Landmark features are naturally occurring as it is not allowed to modify the environment with special navigational aids. These features are sparse in our application domain and are frequently occluded by other robots. This makes simultaneous acquisition of two or more landmarks difficult. Therefore, we propose a system that requires a single landmark feature. The algorithm is based on range measurement of a single landmark from two arbitrary points whose displacement can be measured using dead-reckoning sensors. Range estimation is done with a stereo vision system. Simulation results show that the robot can localize itself if it can estimates range of the same landmark from two different position and if the displacement between the two position is known.

关键词： Mobile robots Robot sensing systems Robot vision systems Cameras Navigation Position measurement Robotics and automation Displacement measurement Educational robots Goniometers

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Online Lidar-Camera Extrinsic Parameters Self-Checking

SSRN

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SSRN 2023年

作者： Wei, Pengjin Yan, Guohang You, Xin Fang, Kun Ma, Tao Yang, Jie Liu, Wei Department of Automation Shanghai Jiao Tong University 800 Dongchuan RD Minhang District China Autonomous Driving Group Shanghai AI Laboratory 129 Longwen RD Xuhui District China Institute of Image Processing and Pattern Recognition China

With the development of neural networks and the increasing popularity of automatic driving, the calibration of the LiDAR and the camera has attracted more and more attention. This calibration task is multi-modal, where the rich color and texture information captured by the camera and the accurate three-dimensional spatial information from the LiDAR is incredibly significant for downstream tasks. In real-world applications, as smart cars roll off the production line, their LiDAR and camera systems are meticulously calibrated, while in the rest of the car life period, the poses of the LiDARs and cameras no longer get continually supervised to ensure the security. To this end, this paper proposes a self-checking algorithm to judge whether the extrinsic parameters are well-calibrated during the car life period by introducing a binary classification network based on the fused information from the camera and the LiDAR. Moreover, since there is no such dataset for the task in this work, we further generate a new dataset branch from the KITTI dataset tailored for the task. Our experiments on the proposed dataset branch demonstrate the performance of our method. To the best of our knowledge, this is the first work to address the significance of continually checking the calibrated extrinsic parameters for autonomous driving. The dataset and code are available at https://***/OpenCalib/LiDAR2camera_self-check © 2023, The Authors. All rights reserved.

关键词： Cameras

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Mobile robot localization under varying illumination

Mobile robot localization under varying illumination

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International Conference on pattern recognition

作者： M. Jogan A. Leonardis H. Wildenauer H. Bischof Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Pattern Recognition and Image Processing Group Institute for Computer Aided Automation University of Technology Vienna Vienna Austria Institute for Computer Graphics and Vision Graz University of Technology Graz Austria

Methods for mobile robot localization that use eigenspaces of panoramic snapshots of the environment are in general sensitive to changes in the illumination of the environment. Therefore, we propose an approach which achieves a reliable localization under severe illumination conditions. The method uses gradient filtering of the eigenspace. After testing the approach on images obtained by a mobile robot, we show that it outperforms the standard eigenspace-based recognition method.

关键词： Mobile robots Lighting Computer vision Filter bank image recognition Indoor environments pattern recognition image processing Computer graphics Information science

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