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

作者： Nenad Tomašev Raluca Brehar Dunja Mladenić Sergiu Nedevschi Jožef Stefan Institute Artificial Intelligence Laboratory Ljubljana Slovenia Image Processing and Pattern Recognition Group Technical University of Cluj-Napoca Romania

Object recognition from images is one of the essential problems in automatic image processing. In this paper we focus specifically on nearest neighbor methods, which are widely used in many practical applications, not necessarily related to image data. It has recently come to attention that high dimensional data also exhibit high hubness, which essentially means that some very influential data points appear and these points are referred to as hubs. Unsurprisingly, hubs play a very important role in the nearest neighbor classification. We examine the hubness of various image data sets, under several different feature representations. We also show that it is possible to exploit the observed hubness and improve the recognition accuracy.

关键词： Feature extraction Object recognition Entropy Histograms Visualization image color analysis Shape

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CROON: Automatic Multi-LiDAR Calibration and Refinement Method in Road Scene

arXiv

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arXiv 2022年

作者： Wei, Pengjin Yan, Guohang Li, Yikang Fang, Kun Cai, Xinyu Yang, Jie Liu, Wei The Institute of Image Processing and Pattern Recognition Department of Automation Shanghai Jiao Tong University China The Autonomous Driving Group Shanghai AI Laboratory China

Sensor-based environmental perception is a crucial part of the autonomous driving system. In order to get an excellent perception of the surrounding environment, an intelligent system would configure multiple LiDARs (3D Light Detection and Ranging) to cover the distant and near space of the car. The precision of perception relies on the quality of sensor calibration. This research aims at developing an accurate, automatic, and robust calibration strategy for multiple LiDAR systems in the general road scene. We thus propose CROON (automatic multi-LiDAR Calibration and Refinement methOd in rOad sceNe), a two-stage method including rough and refinement calibration. The first stage can calibrate the sensor from an arbitrary initial pose, and the second stage is able to precisely calibrate the sensor iteratively. Specifically, CROON utilize the nature characteristics of road scene so that it is independent and easy to apply in large-scale conditions. Experimental results on real-world and simulated data sets demonstrate the reliability and accuracy of our method. All the related data sets and codes are open-sourced on the Github website https://***/OpenCalib/LiDAR2LiDAR. Copyright © 2022, The Authors. All rights reserved.

关键词： Intelligent systems

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Nearness in digital images and proximity spaces

Nearness in digital images and proximity spaces

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9th International Conference on Discrete Geometry for Computer imagery, DGCI 2000

作者： Pták, Pavel Kropatsch, Walter G. CMP – Czech Technical University Center for Machine Perception Karlovo nám. 13 Praha 2121 35 Czech Republic Institute of Computer Aided Automation 183/2 Vienna University of Technology Pattern Recognition and Image Processing Group Favoritenstr.9 WienA-1040 Austria

ISBN: (纸本)3540413960

The concept of "nearness", which has been dealt with as soon as one started studying digital images, finds one of its rigorous forms in the notion of proximity space. It is this notion, together with "nearness preserving mappings", that we investigate in this paper. We first review basic examples as they naturally occur in digital topologies, making also brief comparison studies with other concepts in digital geometry. After this we characterize proximally continuous mappings in metric spaces. Finally, we show by example that the "proximite complexity" of a finite covering in a digital picture may be too high to be adequately depicted in a finite topological space. This combinatorial result may indicate another conceptual advantage of proximities over topologies. © Springer-Verlag Berlin Heidelberg 2000.

关键词： Topology

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Automated multi-contrast brain pathological area extraction from 2D MR images

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Journal of Applied Research and Technology 2015年第1期13卷 58-69页

作者： Dvořák, P. Bartušek, K. Kropatsch, W.G. Smékal, Z. Institute of Scientific Instruments of the ASCR V.v.i Academy if Sciences of the Czech Republic Brno Czech Republic Dept. of Telecommunications Faculty of Electrical Engineering and Communication Brno University of Technology Brno Czech Republic Pattern Recognition and Image Processing Group Institute of Computer Graphics and Algorithms Faculty of Informatics Vienna University of Technology Vienna Austria

The aim of this work is to propose the fully automated pathological area extraction from multi-parametric 2D MR images of brain. The proposed method is based on multi-resolution symmetry analysis and automatic thresholding. The proposed algorithm first detects the presence of pathology and then starts its extraction. T2 images are used for the presence detection and the multi-contrast MRI is used for the extraction, concretely T2 and FLAIR images. The extraction is based on thresholding, where Otsu's algorithm is used for the automatic determination of the threshold. Since the method is based on symmetry, it works for both axial and coronal planes. In both these planes of healthy brain, the approximate left-right symmetry exists and it is used as the prior knowledge for searching the approximate pathology location. It is assumed that this area is not located symmetrically in both hemispheres, which is met in most cases. The detection algorithm was tested on 203 T2-weighted images and reached the true positive rate of 87.52% and true negative rate of 93.14%. The extraction algorithm was tested on 357 axial and 443 coronal real images from publicly available BRATS databases containing 3D volumes brain tumor patients. The results were evaluated by Dice Coefficient (axial: 0.85 ± 0.11, coronal 0.82 ± 0.18) and by Accuracy (axial: 0.96 ± 0.05, coronal 0.94 ± 0.09). © 2015 Universidad Nacional Autónoma de México.

关键词： Brain Pathology Brain Tumor MRI Multi-contrast MRI Symmetry Analysis

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A robust matching algorithm for active appearance models 1

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Workshops Bildverarbeitung fur die Medizin: Algorithmen - Systeme - Anwendungen, BVM 2005 - Workshop on image processing for Medicine: Algorithms - Systems - Applications, BVM 2005

作者： Beichel, Reinhard Bischof, Horst Langs, Georg Sonka, Milan Institute for Computer Graphics and Vision Graz University of Technology Inffeldgasse 16/2 A-8010 Graz Austria Pattern Recognition and Image Processing Group Vienna University of Technology Favoritenstr. 9 A-1040 Vienna Austria Department of Electrical and Computer Engineering University of Iowa Iowa City IA 52242 United States

ISBN: (数字)9783540264316

ISBN: (纸本)3540250522

This paper proposes a method for robustly matching active appearance models (AAMs) on images with gross disturbances (outliers). The method consists of two steps. First, an initial residual is calculated by comparing model and image appearance, and modes of the residual are analyzed. Second, all possible mode combinations are tested by evaluating an objective function. The objective function allows the selection of an outlier-free mode combination. Experiments demonstrate the ability of the robust matching method to successfully cope with outliers - compared to standard AAM matching, no degeneration of the model during matching occurs.

关键词： Statistics

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A real-time algorithm for train position monitoring using optical time-domain reflectometry

A real-time algorithm for train position monitoring using op...

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IEEE International Conference on Intelligent Rail Transportation (ICIRT)

作者： Adam Papp Christoph Wiesmeyr Martin Litzenberger Heinrich Garn Walter Kropatsch Digital Safety and Security Department Austrian Institute of Technology GmbH Vienna Austria Pattern Recognition and Image Processing group Vienna University of Technology Vienna Austria

ISBN: (纸本)9781509015566

We propose an algorithm which uses an optical time-domain reflectometer (OTDR) for real-time tracking of trains. OTDR sensing, often also termed distributed acoustical sensing (DAS), measures the Rayleigh backscattering of a light pulse along an optical fiber. The resulting signal provides information on local acoustic pressure at linearly spaced positions along the fiber. While different approaches for train tracking with DAS are described in the literature, the results have been evaluated only for short time recordings with few train crossings. In this paper we provide details on the tracking performance of a novel algorithm that finds and tracks trains over 15km. Furthermore, this is the first contribution that uses ground truth data to assess the performance of the method. For the evaluation two one hour recordings are used.

关键词： Monitoring Vibrations Optical fibers Sensors Backscatter Rail transportation Time measurement

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A Hybrid Approach Towards Vision Based Self-localization of Autonomous Mobile Robots

A Hybrid Approach Towards Vision Based Self-localization of ...

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International Conference on Machine Vision (ICMV 2007)

作者： Abdul Bais Robert Sablatnig Yahya M. Khawaja Ghulam M. Hassan Department of Computer Systems Engineering NWFP University of Engineering and Technology Peshawar Pakistan Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria

This paper presents a hybrid approach towards self-localization of tiny autonomous mobile robots in a known but highly dynamic environment. The proposed algorithm is intended for two-wheeled differential drive robots which are equipped with a pivoted stereo vision system, two digital encoders, a gyro sensor, two 10g accelerometers and a magnetic compass. The global position of the robot can be estimated by extracting two distinct landmarks from the robot environment and measuring their range and orientation using the stereo vision system. However, distinct landmarks are not available through the entire state space and it is required to track the robot position once a global estimate is available. Tracking of the globally estimated position is performed within the framework of extended Kalman filter. Constant monitoring of the robot observation enables it to detect any unexpected situation. Simulation results show that robot can successfully localize itself at startup and is capable of detecting and recovering from localization failures.

关键词： Mobile robots Orbital robotics Robot sensing systems Robot vision systems Stereo vision Magnetic sensors Sensor systems Accelerometers Position measurement State-space methods

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Discovering structural regularity in facade image

Discovering structural regularity in facade image

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IEEE International Conference on Systems, Man and Cybernetics

作者： Weiwei Li Xin Zheng Jie Chen Image Processing and Pattern Recognition College of Information Science and Technology Beijing Normal University Beijing China Information Center CITIC Guoan Group Beijing China

3D reconstruction from single view is a very difficult problem in computer vision and computer graphics. Few works have been done in this area. In this paper, we proposed a method to discover structural regularity in single facade images on the procedural modeling of buildings by using SIFT algorithm. Firstly, symmetry information is detected from the image using SIFT algorithm for image analysis. Next, the symmetry information will be removed from the facade image. Finally, get the SIFT feature of widows and doors. Experiments show that our method can successfully discover regular structures with a higher recognition rate than existing method especially amidst shadowing and the changing illumination environment.

关键词： Laboratories

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Constructing stochastic pyramids by MIDES – maximal independent directed edge set

Constructing stochastic pyramids by MIDES – maximal indepen...

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4th IAPR International Workshop on Graph Based Representations in pattern recognition, GbRPR 2003

作者： Haxhimusa, Yll Glantz, Roland Kropatsch, Walter G. Pattern Recognition and Image Processing Group 183/2 Institute for Computer Aided Automation Vienna University of Technology Favoritenstrasse 9 ViennaA-1040 Austria Dipartimento di Informatica Università di Ca’ Foscari di Venezia Via Torino 155 MestreVE30172 Italy

ISBN: (纸本)354040452X

We present a new method (MIDES) to determine contraction kernels for the construction of graph pyramids. Experimentally the new method has a reduction factor higher than 2.0. Thus, the new method yields a higher reduction factor than the stochastic decimation algorithm (MIS) and maximal independent edge set (MIES), in all tests. This means the number of vertices in the subgraph induced by any set of contractible edges is reduced to half or less by a single parallel contraction. The lower bound of the reduction factor becomes crucial with large images. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Directed graphs

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Content based image retrieval using interest points and texture features

Content based image retrieval using interest points and text...

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International Conference on pattern recognition

作者： C. Wolf J.-M. Jolion W. Kropatsch H. Bischof Pattern Recognition and Image Processing Group University of Technology Vienna Wien Austria Laboratoire Reconnaissance de Formes et Vision INSA Lyon Villeurbanne France

ISBN: (纸本)0769507506

Content based image retrieval is the task of searching images from a database, which are visually similar to a given example image. We present methods for content based image retrieval based on texture similarity using interest points and Gabor features. Interest point detectors are used in computer vision to detect image points with special properties, which can be geometric (corners) or non-geometric (contrast etc.). Gabor functions and Gabor filters are regarded as excellent tools for feature extraction and texture segmentation. The article combines these methods and generates a textural description of images. Special emphasis is devoted to distance measures on texture descriptions. Experimental results of a query system are given.

关键词： image retrieval Content based retrieval Information retrieval image databases Spatial databases Visual databases Detectors Computer vision Gabor filters Feature extraction

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