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International Conference on image Analysis and processing

作者： Jarmo Ilonen Joni-Kristian Kamarainen Heikki Kalviainen Machine Vision and Pattern Recognition Research Group Lappeenranta University of Technology Finland Centre for Vision Speech and Signal Processing University of Surrey UK

Gabor filter responses are general purpose features for computer vision and image processing and have been very successful in many application areas, for example in bio- metric authentication (fingerprint matching, face detection, face recognition and iris recognition). In a typical feature construction, filters are utilised as a multi-resolution structure of several filters tuned to different frequencies and orientations. The multi-resolution structure is similar to wavelets, but the non-orthogonality of Gabor functions implies the main weakness: computational heaviness. The high computational complexity prevents their use in many real-time or near real-time tasks. In this study, an efficient sequential computation method for multi-resolution Gabor features is presented.

关键词： Gabor filters Computer vision image processing Application software Authentication Fingerprint recognition Face detection Face recognition Iris recognition Frequency

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A comparision of Model-based methods for knee cartilage segmentation

A comparision of Model-based methods for knee cartilage segm...

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2nd International Conference on Computer Vision Theory and Applications, VISAPP 2007

作者： Cheong, J. Faggian, N. Langs, G. Suter, D. Cicuttini, F. Dept. of Electrical Dept. of Computer Systems Engineering Monash University Australia Clayton School of Information Technology Monash University Australia Institute for Computer Graphics and Vision Graz University of Technology Austria Pattern Recognition and Image Processing Group Vienna University of Technology Austria Dept. of Epidemiology Dept. of Preventive Medicine Monash University Australia

Osteoarthritis is a chronic and crippling disease affecting an increasing number of people each year. With no known cure, it is expected to reach epidemic proportions in the near future. Accurate segmentation of knee cartilage from magnetic resonance imaging (MRI) scans facilitates the measurement of cartilage volume present in a patient's knee, thus enabling medical clinicians to detect the onset of osteoarthritis and also crucially, to study its effects. This paper compares four model-based segmentation methods popular for medical data segmentation, namely Active Shape Models (ASM) (Cootes et al., 1995), Active Appearance Models (AAM) (Cootes et al., 2001), Patch-based Active Appearance Models (PAAM) (Faggian et al., 2006), and Active Feature Models (AFM) (Langs et al., 2006). A comprehensive analysis of how accurately these methods segment human tibial cartilage is presented. The results obtained were benchmarked against the current "gold standard" (cartilage segmented manually by trained clinicians) and indicate that modeling local texture features around each landmark provides the best results for segmenting human tibial cartilage.

关键词： Medical imaging

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Object Localisation Using Generative Probability Model for Spatial Constellation and Local image Features

Object Localisation Using Generative Probability Model for S...

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International Conference on Computer Vision (ICCV)

作者： J.-K. Kamarainen M. Hamouz J. Kittler P. Paalanen J. Ilonen A. Drobchenko Centre for Vision Speech and Signal Processing (CVSSP) University of Surrey UK Machine Vision and Pattern Recognition Research Group Lappeenranta University of Technology Finland

In this paper we apply state-of-the-art approach to object detection and localisation by incorporating local descriptors and their spatial configuration into a generative probability model. In contrast to the recent semi- supervised methods we do not utilise interest point detectors, but apply a supervised approach where local image features (landmarks) are annotated in a training set and therefore their appearance and spatial variation can be learnt. Our method enables working in purely probabilistic search spaces providing a MAP estimate of object location, and in contrast to the recent methods, no background class needs to be formed. Using the training set we can estimate pdfs for both spatial constellation and local feature appearance. By applying an inference bias that the largest pdf mode has probability one, we are able to combine prior information (spatial configuration of the features) and observations (image feature appearance) into posterior distribution which can be generatively sampled, e.g. using MCMC techniques. The MCMC methods are sensitive to initialisation, but as a solution, we also propose a very efficient and accurate RANSAC-based method for finding good initial hypotheses of object poses. The complete method can robustly and accurately detect and localise objects under any homography.

关键词： Object detection Robustness Solid modeling Speech processing Signal processing Machine vision pattern recognition Signal generators Detectors Phase detection

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Multi-label image segmentation via max-sum solver

Multi-label image segmentation via max-sum solver

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Conference on Computer Vision and pattern recognition (CVPR)

作者： Banislav Micusik Tomas Pajdla Pattern Recognition and Image Processing Group Inst. of Computer Aided Automation University of Technology Vienna Austria Center for Machine Perception Dpt. of Cybernetics Czech Technical University Czech Republic

We formulate single-image multi-label segmentation into regions coherent in texture and color as a MAX-SUM problem for which efficient linear programming based solvers have recently appeared. By handling more than two labels, we go beyond widespread binary segmentation methods, e.g., MIN-CUT or normalized cut based approaches. We show that the MAX-SUM solver is a very powerful tool for obtaining the MAP estimate of a Markov random field (MRF). We build the MRF on superpixels to speed up the segmentation while preserving color and texture. We propose new quality functions for setting the MRF, exploiting priors from small representative image seeds, provided either manually or automatically. We show that the proposed automatic segmentation method outperforms previous techniques in terms of the global consistency error evaluated on the Berkeley segmentation database.

关键词： image segmentation image databases Belief propagation pattern recognition image processing Automation Cybernetics Color Linear programming Markov random fields

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Example-Based Logical Labeling of Document Title Page images

Example-Based Logical Labeling of Document Title Page Images

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International Conference on Document Analysis and recognition

作者： J. van Beusekom D. Keysers F. Shafait T. Breuel Technical University of Kaiserslautern Germany German Research Center for Artificial Intelligence (DFKI) Kaiserslautern Germany Image Understanding and Pattern Recognition (IUPR) Research Group Technical University of Kaiserslautern Germany

This paper presents a flexible and effective example- based approach for labeling title pages which can be used for automated extraction of bibliographic data. The labels of interest are "title", "author", "abstract" and "affiliation". The method takes a set of labeled document layouts and a single unlabeled document layout as input and finds the best matching layout in the set. The labels of this layout are used to label the new layout. The similarity measure for layouts combines structural layout similarity and textural similarity on the block-level. Experimental results yield accuracy rates from 94.8% to 99.6% obtained on the publicly available MARG dataset. This shows that our lightweight method has equivalent and partially better performance when compared to other more complex labeling methods known from the literature.

关键词： Layout Labeling Databases Adaptation models Hidden Markov models Histograms image segmentation

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Robust real-time tracking for visual surveillance

Eurasip Journal on Advances in Signal Processing

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Eurasip Journal on Advances in Signal processing 2007年 2007卷

作者： Thirde, David Borg, Mark Aguilera, Josep Wildenauer, Horst Ferryman, James Kampel, Martin School of Systems Engineering Computational Vision Group University of Reading Reading RG6 6AY United Kingdom Computer Science Department Pattern Recognition and Image Processing Group Vienna University of Technology Vienna 1040 Austria

This paper describes a real-time multi-camera surveillance system that can be applied to a range of application domains. This integrated system is designed to observe crowded scenes and has mechanisms to improve tracking of objects that are in close proximity. The four component modules described in this paper are (i) motion detection using a layered background model, (ii)object tracking based on local appearance, (iii) hierarchical object recognition, and (iv) fused multisensor object tracking using multiple features and geometric constraints. This integrated approach to complex scene tracking is validated against a number of representative real-world scenarios to show that robust, real-time analysis can be performed. Copyright © 2007 Hindawi Publishing Corporation. All rights reserved.

关键词： Tracking (position)

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Editorial: Knowledge engineering, semantics, and signal processing in audio - visual information retrieval

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IEEE Transactions on Circuits and Systems for Video Technology 2007年第3期17卷 257-258页

作者： Izquierdo, Ebroul Zhang, Jian Sikora, Thomas Huang, Thomas S. Department of Electrical Engineering Queen Mary University of London London El 4NS United Kingdom Sydney Australia School of Computer Science and Engineering University of New South Wales Australia Communication Systems Group Technical University Berlin Berlin Germany ITG University of Illinois at Urbana-Champaign United States Department of Electrical and Computer Engineering Coordinated Science Laboratory United States Image Formation and Processing Group Beckman Institute for Advanced Science and Technology United States Institute's Major Research Theme Human Computer Intelligent Interaction National Academy of Engineering Chinese Academies of Engineering and Sciences China International Association of Pattern Recognition Optical Society of American United States

No abstract available

关键词： Special issues and sections Knowledge engineering Information retrieval Audio-visual systems

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A Tongue-Print image Database for recognition

A Tongue-Print Image Database for Recognition

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Zhi Liu Jing-Qi Yan David Zhang Qun-Lin Tang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University hanghai China Biometrics Research Centre Hong Kong Polytechnic University Kowloon Hong Kong The Graduate School of Harbin Institute of Technology Shenzhen China

The tongue is a unique organ in that it can be stuck out of mouth for inspection, in this act offering a proof of life, and yet it is otherwise well protected in the mouth and is difficult to forge. The tongue also presents both geometric shape information and physiological texture information which are potentially useful in identity verification applications. Furthermore, the act of physically reaching or thrusting out is a convincing proof for the liveness. Despite these obvious advantages, little work has hitherto been done on tongue features. A primary factor for preventing such research is the lack of an available 3D tongue image database. In this paper, we present a newly developed 3D tongue image database, which includes both tongue geometric shape and surface textures of 134 subjects. This is the first attempt at making a 3D tongue image database available for the research community, with the ultimate goal of fostering the research on tongue biometrics. The new database can be a valuable resource for algorithm assessment, comparison and evaluation.

关键词： image databases image recognition Tongue Mouth Shape Inspection Protection Surface texture Biometrics Spatial databases

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Motion Analysis of Endovascular Stent-Grafts by MDL Based Registration

Motion Analysis of Endovascular Stent-Grafts by MDL Based Re...

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International Conference on Computer Vision (ICCV)

作者： Georg Langs Nikos Paragios Rene Donner Pascal Desgranges Alain Rahmouni Hicham Kobeiter GALEN Group Laboratoire de Mathématiques Appliquées aux Systàmes Ecole Centrale de Paris France Institute for Computer Graphics and Vision Graz University of Technology Austria Pattern Recognition and Image Processing Group University of Technology Vienna Austria University of Paris XII Paris France

The endovascular repair of a traumatic rupture of the thoracic aorta - that would otherwise lead to the death of the patient - is performed by delivering a stent-graft into the vessel at the rupture location. The age range of the affected patients is large and the stent-graft will stay in the body for the remaining life. The technique is relatively new, and no experience with regard to long-term effects, and durability exists. To predict long-term complications, such as ruptures or destructive interactions with surrounding tissue during the life of the patient, it is important to understand the - rather intense and constant - movement of the stent- graft during the cardiac cycle. A computed tomography with heart gating (gated CT) acquires sequences that show the region of the stent-graft at different time points. We analyze the motion of stent-grafts with a model based approach. Stent-grafts are represented as sparse sets of axis points extracted from the gated CT, and motion patterns are captured by a minimum description length based group-wise registration of the stent-graft at different time points. No parameterization or a priori definition of the topology is necessary, and highly variable elasticity properties in the data volume can by accounted for by the sparse statistical model, that captures correlations and motion components of the stent-graft. We report results for deformation models and registration accuracy for 5 patients.

关键词： Motion analysis Computed tomography Biomedical imaging Heart Buildings Computer graphics pattern recognition image processing Hospitals Data mining

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Humanoid Robot 3 -D Motion Simulation for Hardware Realization

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Journal of Donghua University 2007年第6期000卷

作者： CAO Xi ZHAO Qun-fei MA Pei-sun Research Institute of Robotics Shanghai Jiaotong UniversityShanghai 200030China Institute of Image Processing & Pattern Recognition Shanghai Jiaotong UniversityShanghai 200030China

In this paper, three dimensions kinematics andkinetics simulation arc discussed for hardware realization ofa physical biped walking-chair robot. The direct and inverseclose-form kinematics solution of the biped walking-chairis deduced. Several gaits are realized with thekinematics solution, including walking straight on levelfloor, going up stair, squatting down and standing up. ZeroMoment Point(ZMP) equation is analyzed considering themovement of the crew. The simulated biped walking-chairrobot is used for mechanical design, gaits development andvalidation before they are tested on real robot.

关键词： Humanoid robot walking chair robot gaitdesign 3D simulation ZMP

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