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A Portable High Resolution Imaging System for Digitizing Large-Surface Paintings

A Portable High Resolution Imaging System for Digitizing Lar...

引用

Congress on image and Signal processing, CISP

作者： Florian Kleber Robert Sablatnig Pattern Recognition and Image Processing Group Institute for Computer Aided Automation University of Technology Vienna Austria

Digitizing large-surface paintings at a high resolution in museums is necessary in the field of painting conservation to document the actual condition of paintings (e.g. colour measurements) and for analysis (e.g. to analyse underdrawings in high-resolution infrared images). Hence, this paper presents a portable system that is able to scan large-surface paintings or images to provide high-resolution digital images. Additional a 3D-model of the surface of the scanned object is generated. The purpose of the 3D-model is to use the 3D-information to create a planar representation of a once planar painting or image that was deformed through environmental effects. Otherwise uncorrected images lead to blurring in the overlap region of the blended subimages. The resolution of the final image is up to 33 pixel/mm and the size of the scanned object is up to 1.5 m x 1.3 m.

关键词： High-resolution imaging Painting Cameras Hardware image resolution image analysis Digital images Fasteners image processing pattern analysis

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Multi-Class Segmentation for Traffic Scenarios at Over 50 FPS

Multi-Class Segmentation for Traffic Scenarios at Over 50 FP...

引用

IEEE Intelligent Vehicles Symposium

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

ISBN: (纸本)9781479936397

Multi-class segmentation assigns a class label to each pixel in an image. It represents a significant task for the semantic understanding of images and has received plentiful attention over the last years. The current state of art is dominated by conditional random field based approaches, defined over pixels or image segments. However, high accuracy segmentation comes at a high computational cost. The best performing methods can barely run at few frames per second and are far from real-time applications. Our goal is to bridge the gap between current state of the art segmentation approaches and real-time applications. In this paper we propose an efficient approach for individual pixel classification. Multiple local descriptors are computed densely and then quantized using visual codebooks. Joint boosting is used to classify each pixel based on the quantized local descriptors. We show that using careful design choices and GPU optimization we can achieve sate of the art segmentation results at over 50 FPS. We also propose a Conditional Random Field (CRF) model defined over superpixels that uses the proposed pixel classifier for the estimation of unary potentials. The CRF based multi-class segmentation can run at over 30 FPS. The proposed approach is validated on the MSRC21 and CamVid multi-class segmentation benchmarks, the former one consisting of urban traffic sequences.

关键词： choices GPU CRF

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Moving rigid objects segmentation in 3D dynamic traffic scenes using a stereovision system

Moving rigid objects segmentation in 3D dynamic traffic scen...

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

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

This paper proposes a novel method for detecting the moving vehicles in dynamic urban traffic scenes using a stereo camera. Relying on the fact that a set of feature points on a rigid 3D scene object are staying in a rigid 3D configuration, we propose to compute the relative motion between the camera and a moving object with an algorithm that follows from the visual odometry based motion estimation methods. Subtracting the camera motion we obtain the absolute object motion. Additionally we create a compact representation of the scene using superpixels computed from intensity and depth information. A graph-like structure is built, having superpixels as nodes and indicating neighboring relationships between adjacent superpixels. Objects are segmented using a fast region growing algorithm that considers as seeds the features used to compute the object motion.

关键词： Three-dimensional displays Visualization Computer vision Cameras Feature extraction Stereo vision image motion analysis

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Single landmark based self-localization of mobile robots

Single landmark based self-localization of mobile robots

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3rd Canadian Conference on Computer and Robot Vision, CRV 2006

作者： Bais, Abdul Sablatnig, Robert Gu, Jason Institute of Computer Technology Vienna University of Technology Vienna Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Vienna University of Technology Vienna Austria Robotics Research Group Department of Electrical and Computer Engineering Dalhousie University Halifax Canada

ISBN: (纸本)0769525423

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. © 2006 IEEE.

关键词： Mobile robots

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Sparse MRF appearance models for fast anatomical structure localisation

Sparse MRF appearance models for fast anatomical structure l...

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2007 18th British Machine Vision Conference, BMVC 2007

作者： Donner, René Mičušsík, Branislav Langs, Georg Bischof, Horst Institute for Computer Graphics and Vision Graz University of Technology Austria Pattern Recognition and Image Processing Group Vienna University of Technology Austria GALEN Group Laboratoire de Mathématiques Appliquées Aux Systèmes Ecole Centrale de Paris France

ISBN: (纸本)1901725340

image segmentation methods like active shape models, active appearance models or snakes require an initialisation that guarantees a considerable overlap with the object to be segmented. In this paper we present an approach that localises anatomical structures in a global manner by means of Markov Random Fields (MRF). It does not need initialisation, but finds the most plausible match of the query structure in the image. It provides for precise, reliable and fast detection of the structure and can serve as initialisation for more detailed segmentation steps. Sparse MRF Appearance Models (SAMs) encode a priori information about the geometric configurations of interest points, local features at these points and local features along the edges of adjacent points. This information is used to formulate a Markov Random Field and the mapping of the modeled object (e.g. a sequence of vertebrae) to the query image interest points is performed by the MAX-SUM algorithm. The local image information is captured by novel symmetry-based interest points and local descriptors derived from Gradient Vector Flow. Experimental results are reported for two data-sets showing the applicability to complex medical data.

关键词： image segmentation

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Color-based and context-aware skin detection for online video annotation

Color-based and context-aware skin detection for online vide...

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IEEE Workshop on Multimedia Signal processing

作者： Christian Liensberger Julian Stottinger Martin Kampel Institute of Computer Aided Automation Pattern Recognition and Image Processing Group University of Technology Vienna Austria

By analyzing the low level features of images only, skin detection in visual data cannot be solved. To compensate for this major drawback of many approaches, we combine a state of the art recognition algorithm with color model based skin detection. Detected faces in videos are the basis for adaptive skin-color models, which are propagated throughout the video, providing a more precise and accurate model in its recognition performance than pure color based approaches. The approach is able to run in real-time and does not need prior data-specific training. We received challenging online videos from an online service provider and use additional videos from public Web platforms covering a grand variety of different skin-colors, illumination circumstances, image quality and difficulty levels. In an extensive evaluation we estimated the best performing parameters and decide on the best model propagation techniques. We show that adaptive model propagation outperforms static low level detection.

关键词： Skin Face detection image analysis Lighting Internet Automation pattern recognition image processing image color analysis pattern analysis

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Exponential image Enhancement in Daytime Fog Conditions

Exponential Image Enhancement in Daytime Fog Conditions

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

作者： Mihai Negru Sergiu Nedevschi Radu Ioan Peter Image Processing and Pattern Recognition Group Computer Science DepartmentTechnical University of Cluj-Napoca head of the Image Processing and Pattern Recognition Group Computer Science DepartmentTechnical University of Cluj-Napoca Mathematics Department Technical University of Cluj-Napoca

The images captured in fog conditions have degraded contrast,that makes current image processing applications sensitive and error *** propose in this paper an efficient single image enhancement algorithm suitable for daytime fog conditions and based on an original mathematical model,for computing the atmospheric veil,that takes into account the variation in fog density to the *** model is inspired by the functions that appear in partition of unity in the differential geometry *** observing images captured in fog conditions,usually the fog has a very low density in front of the camera and this density has a non-linear increase with the distance,such that objects are no longer visible at greater *** using our mathematical model we are able to obtain superior reconstructions of the original fog-free image,when comparing to traditional *** advantage of our method is the ability to adapt the model in accordance to the density of the fog.A quantitative and qualitative evaluation is performed on both synthetic and real camera *** evaluation proves that our mathematical model is more suitable for image enhancement in both homogeneous and heterogeneous fog *** algorithm is able to perform image enhancement in real time for both color and gray scale images.

关键词： image Exponential image Enhancement in Daytime Fog Conditions

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Propagation of uncertainty in landmark based self-localization of autonomous mobile robots

Propagation of uncertainty in landmark based self-localizati...

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10th IAPR Conference on Machine Vision Applications, MVA 2007

作者： Bais, Abdul Sablatnig, Robert Khawaja, Yahya M. Novak, Gregor Institute of Computer Technology Vienna University of Technology Vienna Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation ViennaUniversity of Technology Vienna Austria Department of Electrical Engineering NWFP University of Engineering and Technology Peshawar Pakistan

ISBN: (纸本)9784901122078

This paper presents uncertainty propagation in landmark based position estimation methods. Analysis of two methods has been carried out where robot position is estimated by detecting one or two globally distinct features using a pivoted stereo vision system. We make a basic assumption about error in estimating point features in camera images and propagate it into robot position estimate using first order approximation of non-linear functions. Simulation results illustrate the performance of the method.

关键词： Stereo image processing

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Evaluation of object tracking for aircraft activity surveillance

Evaluation of object tracking for aircraft activity surveill...

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

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

This paper presents the evaluation of an object tracking system that has been developed in the context of aircraft activity monitoring. The overall tracking system comprises three main modules - motion detection, object tracking and data fusion. In this paper we primarily focus on performance evaluation of the object tracking module, with emphasis given to the general 2D tracking performance and the 3D object localisation.

关键词： Aircraft Surveillance Tracking Motion detection Layout Karhunen-Loeve transforms Computer vision Object detection pattern recognition image processing

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Minimizing the topological structure of line images 7th

Minimizing the topological structure of line images

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7th Joint IAPR International Workshop on Structural and Syntactic pattern recognition, SSPR 1998 and 2nd International Workshop on Statistical Techniques in pattern recognition, SPR 1998

作者： Kropatsch, Walter G. Burge, Mark Vienna University of Technology Institute of Automation 183/2 Pattern Recognition and Image Processing Group Treitlstr.3 WienA-1040 Austria Johannes Kepler University Institute of Systems Science Computer Vision Laboratory LinzA-4040 Austria

ISBN: (纸本)3540648585

We present a new algorithm based on Dual Graph Contraction (DGC) to transform the Run Graph into its Minimum Line Property Preserving (MLPP) form which, when implemented in parallel, requires O(log(longestcurve)) steps. A MLPP graph of a line image compliments the structural information in geometric graph representations like the run graph. Using such a graph and its dual, line image analysis systems can efficiently detect topological features like loops and holes and make use of relations like containment. © Springer-Verlag Berlin Heidelberg 1998.

关键词： Topology

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