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International Conference on Network-Based Information Systems (NBIS)

作者： Tomasz Hachaj Marek R. Ogiela Katarzyna Koptyra Pedagogical University of Krakow Institute of Computer Science and Computer Methods Krakow Poland Cryptography and Cognitive Informatics Research Group AGH University of Science and Technology Krakow Poland

The aim of this research is to evaluate effectiveness of Kinect and Kinect 2 for recognition of specialized actions namely Oyama karate techniques. As a classification algorithm we have used Gesture Description Language (GDL) classifier. We have recorded a dataset that contains motion (MoCap) recordings of two professional sport (black belt) instructors and masters of Oyama Karate. The whole dataset contained 200 movement samples per person (400 samples per Kinect camera, so totally we had 800 samples). After data was captured it was split into two subsets: training and validation. Each subset contained only recordings of a single user. We have performed 2-fold cross validation switching the role of user data between training and validation set. In all cases but two MoCap data from Kinect 2 appeared to be more reliable than from Kinect 1 taking into account both recognition rates of GDL classifier and error classification cases. Also in case of Kinect 1 standard deviation of results were higher which means that classifier becomes less stable while trained on data from older device. The ability of more accurate calculation of legs joints positions seems to be biggest advantages of Kinect 2 over its predecessor.

关键词： Skeleton Cameras Standards computers Electronic mail Classification algorithms Belts

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The Touchless Person Authentication Using Gesture-Types Emulation of Handwritten Signature Templates

The Touchless Person Authentication Using Gesture-Types Emul...

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International Conference on Broadband, Wireless Computing, Communication and Applications (BWCCA)

作者： Marcin Piekarczyk Marek R. Ogiela Institute of Computer Science and Computer Methods Pedagogical University of Cracow Krakow Poland AGH university of of Science and Technology Cryptography and Cognitive Informatics Research Group Krakow Poland

ISBN: (纸本)9781467383165

The paper proposes a secure real-time user authentication system based on dynamic handwritten signature verification. We discuss the touch-less sensor-based authentication mechanism that relies on remote tracking palm-gestures imitating the handwritten signature pattern of examined person. The appropriate data is gathered from non-invasive sensor device in the form of time-ordered series related to spatial coordinates of the pen-like tool position and velocity. The proposed matching scheme exploits data series analysis in joint with feature-based classification. The discrete cosine transform is used to deal with instability of the genuine patterns. We also consider of using the local sensitivity hashing functions to obtain the better efficiency. The detailed analysis of the experimental results is included, too.

关键词： Authentication Discrete cosine transforms Handwriting recognition Data acquisition Databases Emulation computer science

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Usability of the Fuzzy Vault Scheme Applied to Predetermined Palm-Based Gestures as a Secure Behavioral Lock

Usability of the Fuzzy Vault Scheme Applied to Predetermined...

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International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC)

作者： Marcin Piekarczyk Marek R. Ogiela Institute of Computer Science and Computer Methods Pedagogical University of Cracow Krakow Poland AGH University of Science and Technology Cryptography and Cognitive Informatics Research Group Krakow Poland

Nowadays, the crypto-biometric schemes are commonly studied to deal with the key management problem existing in cryptographic systems. In the paper we consider a well-known fuzzy vault scheme working on non-standard biometric data associated with palm-oriented gestures. We discuss the usefulness of the touch-less palm tracking system focused on handling the biomechanical characteristics of one's hand to protect the cryptographic key or other secret data. As a behavioral template the fixed finger-based gesture is applied. In order to generate unordered sets for fuzzy vault we use the global approach where features are decoded from fingertip position and velocity. Both the raw and DCT-calculated time series are preprocessed to solve the instability and variability problem strictly related to behavioral character of the data. We provide the experimental results and discuss the security issues.

关键词： Cryptography Bioinformatics Encoding Quantization (signal) Usability Cyclic redundancy check codes

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Application of hidden markov models and gesture description language classifiers to Oyama karate techniques recognition

Application of hidden markov models and gesture description ...

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International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS)

作者： Tomasz Hachaj Marek R. Ogiela Katarzyna Koptyra Pedagogical University of Krakow Institute of Computer Science and Computer Methods Krakow Poland AGH University of Science and Technology Cryptography and Cognitive Informatics Research Group Krakow Poland

The karate movements classification is extremely challenging task due to the speed of body movements. From the other hand movements patterns are highly repetitive because they are practiced for many years by skilled martial artists. Those two facts make karate techniques classification tasks reliable tests of classifiers potential. Also, nowadays there is a growing interest on commercial market for solutions that are capable to be used in computer entertainment and coaching systems. Those factors motivated us to evaluate our Gesture Description Language (GDL) classifier trained with unsupervised reversed-GDL (R-GDL) method on karate techniques dataset and to compare it with state-of-the-art approach namely multivariate continuous hidden Markov model classifier with Gaussian distribution. The evaluation of capability of R-GDL methodology to karate techniques classification is main novelty of this paper. We have achieved very promising results. Only one class of actions has average recognition rate on the level of 88% while other where between 90% and 100%. GDL has also important advantages over state-of-the-art HMM classier that we will discuss in this paper.

关键词： Hidden Markov models Training Joints Pattern recognition

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Human Actions Modelling and Recognition in Low-Dimensional Feature Space

Human Actions Modelling and Recognition in Low-Dimensional F...

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International Conference on Broadband, Wireless Computing, Communication and Applications (BWCCA)

ISBN: (纸本)9781467383165

The aim of this paper is to prove that it is possible to model the set of multiple human actions in low-dimensional feature space so they can be nearly unambiguously distinguish with the help of classification algorithm. The most important condition that has to be satisfied to solve this problem is selection of proper features sets that fit to a particular actions group. We evaluate our methodology on the dataset consisted of 16 different Oyama Karate techniques performed by two professional sport (black belt) instructors and masters of Oyama Karate. The dataset consisted of 640 actions samples. As a classification algorithm we have used Gesture Description Language. We have used four different angle-based features sets. With that selection we have made actions descriptions that transformed initial motion capture dataset to 6 or 8 dimensional features space with maximally three keyframes. Beside only one class the recognition rate was at level of 88% to even 100%.

关键词： Skeleton Classification algorithms Trajectory Torso Principal component analysis Computational modeling Support vector machines

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Novel J-PET scanner combined with positron annihilation lifetime spectroscopy technique as a tool for morphometric imaging

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Physica Medica 2016年 32卷 231-232页

作者： Ewelina Kubicz D. Alfs T. Bednarski P. Białas E. Czerwiński A. Gajos B. Głowacz M. Gorgol B. Jasińska D. Kamińska G. Korcyl P. Kowalski T. Kozik W. Krzemień M. Mohammed M. Pawlik-Niedźwiecka S. Niedźwiecki M. Pałka L. Raczyński Z. Rudy P. Moskal Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University S. Łojasiewicza 11 30-348 Kraków Poland Department of Nuclear Methods Institute of Physics Maria Curie-Sklodowska University Pl. M. Curie-Sklodowskiej 1 20-031 Lublin Poland High Energy Physics Division National Centre for Nuclear Research A. Soltana 7 05-400 Otwock-Świerk Poland Świerk Computing Centre National Centre for Nuclear Research A. Soltana 7 05-400 Otwock-Świerk Poland

Positron Annihilation Lifetime Spectroscopy (PALS) allows examining structure of materials at nano and sub-nanometer level. This technique is based on the lifetime and production intensity of ortho-positronium atoms in free volumes of given structures. It is mostly used for studies of organic materials. However there exist also few results, e.g. by groups of Y. C. Jean and R. Pietrzak, showing that morphology of cells is correlated with the PALS parameters. Jagiellonian Positron Emission Tomograph (J-PET) is a multi-purpose detector which will be used for investigations with positronium atoms in life-sciences as well as for medical diagnostics. Such prototype based on plastic scintillators and fully compatible with MRI is currently being developed at the Jagiellonian University in Krakow, Poland. In this talk results of the first experiments conducted by the J-PET collaboration will be presented. We performed PALS studies of well known structures such as silica and of some model micro-organisms, e.g. Saccharomyces cerevisiae both with dry and aqueous samples allowing to determine the correlation between hygroscopicity of the cell and PALS parameters. As a result, we proved that PALS can be successfully used for studies of living organisms their dynamics and its relation to the cells morphology. This result opens perspective for simultaneous determination of early and advanced stages of carcinogenesis by observing changes in biomechanical parameters between normal and tumour cells and standard PET examination. J-PET detection system combined with PALS technique will be more accurate and affordable for cancer diagnostics . Disclosure Authors disclose any relationship that may bias the presentation.

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πη photoproduction on the nucleon

Acta Physica Polonica B, Proceedings Supplement

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Acta Physica Polonica B, Proceedings Supplement 2015年第2期8卷 419-424页

作者： Bibrzycki, Lukasz Kamiński, Robert Department of Computer Science and Computational Methods Pedagogical University of Cracow Podchorazych 2 Kraków30-084 Poland Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of Sciences Radzikowskiego 152 Kraków31-342 Poland

We calculate the amplitude of the πη photoproduction on the proton and the associated cross sections. The primary objective of the model is to describe the photoproduction of the isovector resonances in the πη channel which is important in the context of elucidating the nature of the scalar a0(980) meson. The model can be also applied to description of the photoproduction of tensor isovector resonance a2(1320).

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2015 Brainhack Proceedings Abstracts

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GIGAscience 2016年第1期5卷 1-26页

作者： [Anonymous] Computational Neuroimaging Lab Center for Biomedical Imaging and Neuromodulation Nathan Kline Institute for Psychiatric Research Orangeburg USA Center for the Developing Brain Child Mind Institute New York USA Centre de Recherche Institut Universitaire de Gériatrie de Montréal Montréal Canada Department of computer science and operational research University of Montreal Montreal Canada Max Planck Research Group for Neuroanatomy & Connectivity Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany SRI International Menlo Park USA Department of Psychiatry and Behavioral Sciences Stanford University Stanford USA Functional Imaging Unit Center for Diagnostic Radiology Unviersity Medicine Greifswald Greifswald Germany Université de Montréal Montréal Canada University of Massachusetts Medical School Worcester USA University of California Berkeley USA Institut Pasteur Paris France University of California San Diego La Jolla USA University of Washington Seattle USA Poldrack Lab Department of Psychology Stanford University Stanford USA Montréal Neurological Institute McGill University and Institute of Pscychology Montréal Canada Douglas Mental Health Institute Montréal Canada Otto-von-Guericke University Magdeburg Germany Montreal Neurological Institute McGill University Montreal Canada University of Hawaii John A. Burns School of Medicine Honolulu USA Oregon Health & Science University Portland USA University of Greifswald Greifswald Germany Duke Institute for Brain Sciences Durham USA Department of Psychology and Neuroscience University of Colorado Boulder USA Institute of Cognitive Neuroscience University College London London United Kingdom Section on Functional Imaging Methods Laboratory of Brain and Cognition National Institute of Mental Health Bethedsa USA City University of New York-Hunter College New York USA Monash Institute of Cognitive and Clinical Neurosciences Monash University Melbourne Australia McGill Centre fo

I1 Introduction to the 2015 Brainhack Proceedings R. Cameron Craddock, Pierre Bellec, Daniel S. Margules, B. Nolan Nichols, Jörg P. Pfannmöller A1 Distributed collaboration: the case for the enhancement of Brainspell’s interface AmanPreet Badhwar, David Kennedy, Jean-Baptiste Poline, Roberto Toro A2 Advancing open science through NiData Ben Cipollini, Ariel Rokem A3 Integrating the Brain Imaging Data Structure (BIDS) standard into C-PAC Daniel Clark, Krzysztof J. Gorgolewski, R. Cameron Craddock A4 Optimized implementations of voxel-wise degree centrality and local functional connectivity density mapping in AFNI R. Cameron Craddock, Daniel J. Clark A5 LORIS: DICOM anonymizer Samir Das, Cécile Madjar, Ayan Sengupta, Zia Mohades A6 Automatic extraction of academic collaborations in neuroimaging Sebastien Dery A7 NiftyView: a zero-footprint web application for viewing DICOM and NIfTI files Weiran Deng A8 Human Connectome Project Minimal Preprocessing Pipelines to Nipype Eric Earl, Damion V. Demeter, Kate Mills, Glad Mihai, Luka Ruzic, Nick Ketz, Andrew Reineberg, Marianne C. Reddan, Anne-Lise Goddings, Javier Gonzalez-Castillo, Krzysztof J. Gorgolewski A9 Generating music with resting-state fMRI data Caroline Froehlich, Gil Dekel, Daniel S. Margulies, R. Cameron Craddock A10 Highly comparable time-series analysis in Nitime Ben D. Fulcher A11 Nipype interfaces in CBRAIN Tristan Glatard, Samir Das, Reza Adalat, Natacha Beck, Rémi Bernard, Najmeh Khalili-Mahani, Pierre Rioux, Marc-Étienne Rousseau, Alan C. Evans A12 DueCredit: automated collection of citations for software, methods, and data Yaroslav O. Halchenko, Matteo Visconti di Oleggio Castello A13 Open source low-cost device to register dog’s heart rate and tail movement Raúl Hernández-Pérez, Edgar A. Morales, Laura V. Cuaya A14 Calculating the Laterality Index Using FSL for Stroke Neuroimaging Data Kaori L. Ito, Sook-Lei Liew A15 Wrapping FreeSurfer 6 for use in high-performance computing environments Hans J. Johns

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An image analysis algorithm for soil structure identification

Advances in Intelligent Systems and Computing

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Advances in Intelligent Systems and Computing 2015年 323卷 681-692页

作者： Charytanowicz, Malgorzata Kulczycki, Piotr Polish Academy of Sciences Systems Research Institute Centre of Information Technology for Data Analysis Methods Newelska 6 Warsaw01-447 Poland Catholic University of Lublin Institute of Mathematics and Computer Science Konstantynow 1H Lublin20-708 Poland Cracow University of Technology Department of Automatic Control and Information Technology Warszawska 24 Cracow31-155 Poland

Pore space study has been utilized as a general method for defining soil structures. This is because the characteristics particular to pore space impact the majority of physical and physicochemical soil parameters relevant due to plant growth. This paper presents an image segmentation approach for detecting the soil pore structures that have been studied by way of soil tomography sections. In so-doing, a research study was conducted using a density-based clustering method, and in turn, the nonparametric kernel estimation methodology. This overcomes the rigidity of arbitrary assumptions concerning the number or shape of clusters among data, and lets the researcher detect inherent data structures. After a short description of the method, the practical aspects and applications illustrated with a number of soil aggregates are presented. © Springer International Publishing Switzerland 2015.

关键词： Image segmentation

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Unsupervised Learning of GDL Classifier

Unsupervised Learning of GDL Classifier

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International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS)

作者： Tomasz Hachaj Marek R. Ogiela Pedagogical University of Krakow Institute of Computer Science and Computer Methods Krakow Poland AGH University of Science and Technology Krakow Poland

GDL (Gesture Description Language) is a pattern recognition method that enables syntactic description and real time recognition of static body poses and movement sequences. The syntax of context free GDL script (GDLs) language is intuitive and easy to learn for new user, however so far GDLs rules had to be implemented without feedback of machine learning methods. In this paper we present proposition and initial evaluation of unsupervised method of GDL classifier learning that enables automatic generation of GDLs descriptions using specified features and sample movements recordings. New automatically generated GDLs are well understandable the same as manually defined descriptions. This property enables easy interpretation of obtained training results in contrast to the results from others popular pattern recognition methods.

关键词： Joints Hidden Markov models Real-time systems Training Gesture recognition

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