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4th International Conference on Computer Vision Theory and Applications

作者： Uray, Martina Roth, Peter M. Bischof, Horst Institute of Digital Image Processing Joanneum Research Austria Institute for Computer Graphics and Vision Graz University of Technology Austria

ISBN: (纸本)9789898111692

In this paper we consider the limitations of Linear Discriminative Analysis (LDA) when applying it for large-scale problems. Since LDA was originally developed for two-class problems the obtained transformation is sub-optimal if multiple classes are considered. In fact, the separability between the classes is reduced, which decreases the classification power. To overcome this problem several approaches including weighting strategies and mixture models were proposed. But these approaches are complex and computational expensive. Moreover, they were only tested for a small number of classes. In contrast, our approach allows to handle a huge number of classes showing excellent classification performance at low computational costs. The main idea is to split the original data into multiple sub-sets and to compute a single LDA space for each sub-set. Thus, the separability in the obtained subspaces is increased and the overall classification power is improved. Moreover, since smaller matrices have to be handled the computational complexity is reduced for both, training and classification. These benefits are demonstrated on different publicly available datasets. In particular, we consider the task of object recognition, where we can handle up to 1000 classes.

关键词： LDA image classification Large databases

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image processing with an array processor

Image processing with an array processor

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Applications of digital image processing V 1983

作者： Ranzinger, Hubert Institute for Digital Image Processing and Graphics Graz Research Centre Wastiangasse 6 Graz8010 Austria

At the Graz Research Centre, an instruction Library for a deAnza IP 6400 image Array Processor has been developed. This library provides easy access the image processing facilities and speeds up algorithm implementation considerably. The paper presents the application of these instructions to some image processing tasks and discusses arithmetic problems arising from the use of eight bit operands. © 1983 Proceedings of SPIE - The International Society for Optical Engineering.

关键词： image processing

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A fast pavement location approach for autonomous car navigation 19

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19th Iberoamerican Congress on Pattern Recognition, CIARP 2014

作者： Rateke, Thiago Justen, Karla A. Chiarella, Vito F. Linhares, Rodrigo T. F. Sobieranski, Antonio Carlos Comunello, Eros von Wangenheim, Aldo Federal University of Santa Catarina Brazil Laboratory of Image Processing and Computer Graphics National Brazilian Institute for Digital Convergence Brazil Federal University of Parana Department of Informatics Brazil

ISBN: (纸本)9783319125671

This paper describes a fast image segmentation approach designed for pavement detection in a moving camera. The method is based on a graph-oriented segmentation approach where gradient information is used temporally as a system of discontinuities to control merging between adjacent regions. The method presumes that the navigable path usually is located at specific positions on the scene, and a predefined set of seed points is used to locate the region of interest. The obtained results shown the proposed approach is able to accurately detect in an inexpensive computation manner the navigable path even in non-optimum scenarios such as miss-painted or unpaved dirt roads. Validation was conducted using a dataset with 701 samples of navigable paths, presenting a very high precision for real-time applications. © Springer International Publishing Switzerland 2014.

关键词： Pavements

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Twin and scratch detection and removal in micrograph images of inconel™718

Twin and scratch detection and removal in micrograph images ...

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Machine Vision Applications in Industrial Inspection XIV

作者： Jakob, Gerhard Rinnhofer, Alfred Bischof, Horst Benesova, Wanda Joanneum Research Institute of Digital Image Processing Wastiangasse 6 8045 Graz Austria Technical University Graz Institute for Computer Graphics and Vision Inffeldgasse 16/II 8010 Graz Austria

ISBN: (纸本)0819461105

Grain size of forged nickel alloy is an important feature for the mechanical properties of the material. For fully automatic grain size evaluation in images of micrographs it is necessary to detect the boundaries of each grain. This grain boundary detection is influenced directly by artifacts like scratches and twins. Twins can be seen as parallel lines inside one grain, whereas a scratch can be identified as a sequence of collinear line segments that can be spread over the whole image. Both kinds of artifacts introduce artificial boundaries inside grains. To avoid wrong grain size evaluation, it is necessary to remove these artifacts prior to the size evaluation process. For the generation of boundary images various algorithms have been tested. The most stable results were achieved by grayscale reconstruction and a subsequent watershed segmentation. A modified line Hough transform with a third dimension in the Hough accumulator space, describing the distance of the parallel lines, is used to directly detect twins. Scratch detection is done by applying the standard line Hough transform followed by a rule based segment detection along the found Hough lines. The results of these operations give a detection rate of more than 90 percent for twins and more than 50 percent for scratches. © 2006 SPIE-IS&T.

关键词： Object recognition

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Virtual colon flattening

Virtual colon flattening

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3rd Joint Eurographics - IEEE TCVG Symposium on Visualization, VisSym 2001

作者： Bartrolí, A. Vilanova Wegenkittl, R. König, A. Gröller, E. Sorantin, E. Institute of Computer Graphics and Algorithms Vienna University of Technology Tiani Medgraph Section of Digital Information and Image Processing Department of Radiology University Hospital Graz Austria

ISBN: (纸本)3211836748

We present a new method to visualize virtual endoscopic views. We propose to flatten the organ by the direct projection of the surface onto a set of cylinders. Two sampling strategies are presented and the introduced distortions are studied. A non-photorealistic technique is presented to enhance the perception of the images. Finally, an approximate but real-time endoscopic fly-through is possible by using the data obtained by the projection technique. © 2001 Eurographics Association. All rights reserved.

关键词： image enhancement

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Vehicular Perception Based on Inertial Sensing: A Structured Mapping of Approaches and Methods

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SN Computer Science 2020年第5期1卷 1-24页

作者： Menegazzo, Jeferson von Wangenheim, Aldo Graduate Program in Computer Science (PPGCC) Image Processing and Computer Graphics Lab (LAPIX) Department of Informatics and Statistics (INE) Brazilian Institute for Digital Convergence (INCoD) Federal University of Santa Catarina (UFSC) Santa Catarina Florianópolis Brazil

In this paper, we present a structured literature mapping of the state-of-the-art of vehicular perception methods and approaches using inertial sensors. An in-depth investigation and classification were performed employing the results of a systematic literature review. The analysis focused on identifying methods that capture signals provided by inertial sensors such as accelerometers and gyroscopes to recognize transient or persistent events associated with the vehicle’s movement. We classified these events into vehicular exteroception, associated with potholes, cracks, speed bumps, pavement type, conservation state;and vehicular proprioception, associated with lane change, braking, skidding, aquaplaning, turning right or left. Through the comprehensive study of publications in a 7-year time window, in addition to the methods, we have also identified their dependency factors, hardware platforms and applications. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Driver behaviour Driving style Inertial sensors Intelligent transport systems Road conditions Road surface anomaly

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Speed Bump Detection Through Inertial Sensors and Deep Learning in a Multi-contextual Analysis

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SN Computer Science 2023年第1期4卷 18页

作者： Menegazzo, Jeferson von Wangenheim, Aldo Graduate Program in Computer Science (PPGCC) Image Processing and Computer Graphics Lab (LAPIX) Brazilian National Institute for Digital Convergence (INCoD) Department of Informatics and Statistics (INE) Federal University of Santa Catarina (UFSC)-Florianópolis Santa Catarina Brazil

Speed bumps are vertical raisings of the road pavement used to force drivers to slow down to ensure greater safety in traffic. However, these obstacles have disadvantages in terms of efficiency and safety, where the presence of speed bumps can affect travel time and fuel consumption, cause traffic jams, delay emergency vehicles, and cause vehicle damage or accidents when not properly signaled. Due to these factors, the availability of geolocation information for these obstacles can benefit several applications in Intelligent Transportation System (ITS), such as Advanced Driver Assistance Systems (ADAS) and autonomous vehicles, allowing to trace more efficient routes or alert the driver of the presence of the obstacle ahead. Speed bump detection applications described in the literature employ cameras or inertial sensors, represented by accelerometers and gyroscopes. While camera-based solutions are mature with evaluation in different contextual conditions, those based on inertial sensors do not offer multi-contextual analyses, being mostly simple applications of proof of concept, not applicable in real-world scenarios. For this reason, in this work, we propose the development of a reliable speed bump detection model based on inertial sensors, capable of operating reliably in contextual variations: different vehicles, driving styles, and environments in which vehicles can travel to. For the model development and validation, we collect nine datasets with contextual variations, using three different vehicles, with three different drivers, in three different environments, in which there are three different surface types, in addition to variations in conservation state and the presence of obstacles and anomalies. The speed bumps are present in two different pavement types, asphalt and cobblestone. We use the collected data in experiments to evaluate aspects such as the influence of the placement of the sensors for vehicle data collection and the data window size. Afterwar

关键词： Autonomous vehicles Deep learning Inertial sensors Intelligent transport systems Road conditions Speed bump

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Fast and accurate environment modeling using three-dimensional occupancy grids

Fast and accurate environment modeling using three-dimension...

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International Conference on Computer Vision Workshops (ICCV Workshops)

作者： Katrin Pirker Matthias Rüther Horst Bischof Gerald Schweighofer Institute for Computer Graphics and Vision University of Technology Graz Austria Institute of Digital Image Processing Joanneum Research GmbH Graz Austria

Building a dense and accurate environment model out of range image data faces problems like sensor noise, extensive memory consumption or computation time. We present an approach which reconstructs 3D environments using a probabilistic occupancy grid in real-time. Operating on depth image pyramids speeds up computation time, whereas a weighted interpolation scheme between neighboring pyramid layers boosts accuracy. In our experiments we compare our method with a state-of-the-art mapping procedure. Our results demonstrate that we achieve better results. Finally, we present its viability by mapping a large indoor environment.

关键词： Cameras Robot sensing systems image resolution Equations Accuracy Mathematical model Computational modeling

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Object recognition using local information content

Object recognition using local information content

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International Conference on Pattern Recognition

作者： G. Fritz L. Paletta H. Bischof Joanneum Research Institute of Digital Image Processing Graz Austria Institute of Computer Graphics and Vision Graz University of Technology Graz Austria

Object identification from local information has recently been investigated with respect to its potential for robust recognition, e.g., in case of partial object occlusions, scale variation, noise, and background clutter in detection tasks. This work contributes to this research by a thorough analysis of the discriminative power of local appearance patterns and by proposing to exploit local information content for object representation and recognition. In a first processing stage, we localize discriminative regions in the object views from a posterior entropy measure, and then derive object models from selected discriminative local patterns. Object recognition is then applied to test patterns with associated low entropy using an efficient voting process. The method is evaluated by various degrees of partial occlusion and Gaussian image noise, resulting in highly robust recognition even in the presence of severe occlusion effects.

关键词： Object recognition Noise robustness Entropy Background noise Object detection Information analysis Pattern analysis Pattern recognition Testing Voting

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digital Snow Mapping In High Relief Terrain Using Sar Data

Digital Snow Mapping In High Relief Terrain Using Sar Data

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： H. Rott D. Strobl Institute of Meteorology and Geophysics University of Innsbruck Innsbruck Austria Institute for Digital Image Processing and Graphics Joanneum Research Forschungsgesellschaft GmbH Graz Austria

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