{"title":"GPU based GMM segmentation of kinect data","authors":"Abdenour Amamra, Tarek Mouats, N. Aouf","doi":"10.1109/ELMAR.2014.6923325","DOIUrl":"https://doi.org/10.1109/ELMAR.2014.6923325","url":null,"abstract":"This paper presents a novel approach for background/foreground segmentation of RGBD data with the Gaussian Mixture Models (GMM). We first start by the background subtraction from the colour and depth images separately. The foregrounds resulting from both streams are then fused for a more accurate detection. Our segmentation solution is implemented on the GPU. Thus, it works at the full frame rate of the sensor (30fps). Test results show its robustness against illumination change, shadows and reflections.","PeriodicalId":424325,"journal":{"name":"Proceedings ELMAR-2014","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125899751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fast and efficient FPGA-based Euro coin identification","authors":"Konstantinos Georgopoulos, I. Papaefstathiou","doi":"10.1109/ELMAR.2014.6923304","DOIUrl":"https://doi.org/10.1109/ELMAR.2014.6923304","url":null,"abstract":"This paper describes an efficient hardware implementation of a cross-correlation algorithm on a Field-Programmable Gate Array (FPGA) platform with the purpose of visually identifying coins. This method has the ability to compare images obtained via a video camera with those stored in memory, thereby, accepting/rejecting coins-under-test at the very high-speed demanded by today's coin validation mechanisms. In addition, the user is offered the option to refresh the FPGA memory, i.e. add/remove coin images, on-site as well as store the test results on a host-machine if desired so. The implementation described here constitutes part of a wider coin-validation system that utilises multiple techniques, such as this, operating inparallel with the sole purpose of Euro-coin identification at an acceptable performance to today's standards and criteria.","PeriodicalId":424325,"journal":{"name":"Proceedings ELMAR-2014","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123889466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Face recognition system with automatic training samples selection using self-organizing map","authors":"V. Jirka, Matej Feder, J. Pavlovičová, M. Oravec","doi":"10.1109/ELMAR.2014.6923306","DOIUrl":"https://doi.org/10.1109/ELMAR.2014.6923306","url":null,"abstract":"The paper deals with evaluation of automatic training samples selection method based on self-organizing map (SOM) in face recognition systems. In earlier paper [1] we presented an approach for automatic training samples selection using various clustering algorithms with good results on the CMU PIE face database. We showed that with the use of SOM we can achieve a good training samples selection. In this paper we further evaluate this approach with the use of face recognition systems based on principal component analysis (PCA) and support vector machines (SVM). We compare the results with random (uncontrolled and controlled) training samples selection and we evaluate the recognition accuracy of each method.","PeriodicalId":424325,"journal":{"name":"Proceedings ELMAR-2014","volume":"464 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116178420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Non parametric tool for vision detection analysis","authors":"Riad Azzam, N. Aouf","doi":"10.1109/ELMAR.2014.6923305","DOIUrl":"https://doi.org/10.1109/ELMAR.2014.6923305","url":null,"abstract":"In this work, we deal with the problem of moving object detection using a non-parametric tool represented by the Gaussian process for classification. The technique used relies on the background subtraction approach for motion detection. In this context, a segmentation step is first implemented for pixel clustering before a binary Gaussian process classifier is applied to determine which pixel cluster those of news images belong to. The unclassified pixels are, therefore, labelled as detected targets. This proposed approach enables motion detection to be completed in a comparatively a short execution time with acceptable results. The results outlined here show the effectiveness of the approach to known background subtraction methods.","PeriodicalId":424325,"journal":{"name":"Proceedings ELMAR-2014","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115930488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Alternative approach in generating cancellable fingerprint by using matrices operations","authors":"R. Mukhaiyar, S. Dlay, W. L. Woo","doi":"10.1109/ELMAR.2014.6923342","DOIUrl":"https://doi.org/10.1109/ELMAR.2014.6923342","url":null,"abstract":"A cancellable biometric system aims to revote a biometric feature of an authorized person when his biometric information is misused by improper. In this system, an established biometric image is transformed to a different feature to distinguish it from the original one. Moreover, this revocable system can regenerate a new transformed cancellable biometric feature if the previous transformed feature is known by someone. These basic concepts are similar with the idea of inverse matrix and elementary row operation in matrices domain. Biometric image as a digital image definitely can be processed in matrices domain. It means that the image is able to be imposed by matrices operations such as inverse matrix operation, elementary row operation, and Kronecker product operation. In matrix, these operations are used for several objectives whether inverting matrix elements, changing rows or columns, or enlarging size of the matrix. On the other hand, the combination of these operations even can produce a non-inversed matrix.","PeriodicalId":424325,"journal":{"name":"Proceedings ELMAR-2014","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131010468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Irina Astrova, Stefan Nitz, Carsten Kleiner, Arne Koschel, Florian Herrmann, Daniel Isern, C. Popp
{"title":"Power-aware notification distribution","authors":"Irina Astrova, Stefan Nitz, Carsten Kleiner, Arne Koschel, Florian Herrmann, Daniel Isern, C. Popp","doi":"10.1109/ELMAR.2014.6923361","DOIUrl":"https://doi.org/10.1109/ELMAR.2014.6923361","url":null,"abstract":"Notification distribution is a great feature to have as: (1) it lets employees receive notifications directly on their mobile devices in near real-time; and (2) it reduces the effort required by IT administrators to manage a diverse fleet of mobile devices and platforms. However, it should take into account the fact that the battery lives of mobile devices have been decreasing a lot over the last past years because other features offered by mobile devices like WiFi, Bluetooth and GPS get drained their batteries very quickly. Therefore, notification distribution should seek to minimize its impact on battery power.","PeriodicalId":424325,"journal":{"name":"Proceedings ELMAR-2014","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116958939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mobile network optimisation for smartphones","authors":"Angelo Gary Markoč, G. Šišul","doi":"10.1109/ELMAR.2014.6923315","DOIUrl":"https://doi.org/10.1109/ELMAR.2014.6923315","url":null,"abstract":"In this paper primary goal was to explain basic network optimization in case of mobile smartphone malfunction in usage of certain functionality. Optimization has been done in a way of tracing smartphone behavior, identifying key areas of problematic behavior and then instructing smartphone to use certain functionality in different way or not to use it at all.","PeriodicalId":424325,"journal":{"name":"Proceedings ELMAR-2014","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123483909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Dumic, S. Grgic, David Jiménez Bermejo, Luís A. da Silva Cruz
{"title":"Benchmark of state of the art objective measures for 3D stereoscopic video quality assessment on the Nantes database","authors":"E. Dumic, S. Grgic, David Jiménez Bermejo, Luís A. da Silva Cruz","doi":"10.1109/ELMAR.2014.6923330","DOIUrl":"https://doi.org/10.1109/ELMAR.2014.6923330","url":null,"abstract":"In this work we present a study on the performance of existing state of the art 2D objective image and video quality measures, tested on the new 3D stereoscopic video NAMA3DS1-COSPAD1 database. Different image and video quality measures have been tested on test material affected by different types of degradations. Results show that in some cases, image quality measures give better results than video quality measures. This paradoxical result means that more effort should be devoted to designing new 3D video quality assessment measures. The results presented and accompanying discussion can be used to motivate and guide future research directed towards definition of effective new 3D stereoscopic video quality measures.","PeriodicalId":424325,"journal":{"name":"Proceedings ELMAR-2014","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126107886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Online English vocabulary learning on different systems for non-English speakers","authors":"Mansour Alshumari, G. Bella","doi":"10.1109/ELMAR.2014.6923374","DOIUrl":"https://doi.org/10.1109/ELMAR.2014.6923374","url":null,"abstract":"This paper introduces an empirical study to investigate and compare learning vocabulary using different interaction systems (static, adaptable and an adaptive) learning websites. The purpose of this study is to measure learning vocabulary achievements on non-English language speakers. The participants were Arabic speakers. The aim of the study is to compare the overall usability of these systems in terms of the number of tasks completed by all students and the number of students completing all of the tasks. These were tested independently by three separate groups, each consisting of 33 students (99 student's total). The results show that there was no difference in terms of usability between the three platforms at the overall level and at the individual level (as measured by the system usability scale (SUS)), but there was a difference in learning achievement; further, there was higher achievement in both the adaptive and adaptable systems compared to the static system.","PeriodicalId":424325,"journal":{"name":"Proceedings ELMAR-2014","volume":"81 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129923970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Babin, M. Spyrantis, A. Pižurica, W. Philips, L. Velicki, Vladimir Zlokolica
{"title":"Pixel profiling for extraction of arteriovenous malformation in 3-D CTA images","authors":"D. Babin, M. Spyrantis, A. Pižurica, W. Philips, L. Velicki, Vladimir Zlokolica","doi":"10.1109/ELMAR.2014.6923346","DOIUrl":"https://doi.org/10.1109/ELMAR.2014.6923346","url":null,"abstract":"Cerebral arteriovenous malformation (AVM) presents a great health threat due to its high probability of rupture which can cause severe brain damage or even death. For planing the embolization procedure of an AVM, the knowledge of the accurate location and size of the malformation is of utmost importance. The main purposes of automatic AVM segmentation are: 1) objective and reproducible segmentation; 2) reduction in processing time (saving resources by requiring less manual work). Furthermore, automatic segmentation with accurate AVM (or aneurysm) characterization were deemed helpful in therapeutic decision making concerning treatment modality (surgical or endovascular). Operator-independent accurate sizing of AVM (aneurysm) would allow strict follow-up until the threshold is reached and the patient referred to treatment. We propose in this paper a novel AVM detection method and a blood vessel tree analysis approach using ordered thinning-based skeletonization. The main contributions are: (1) a new method of profile volume calculation to replace the distance labels in ordered skeletonization; (2) an automatic method for AVM detection and extraction, with accurate positioning and malformation size estimation. The main idea in our work is use the structural (anatomical) vessel differences and the inhomogeneities in distribution of pixel gray values to locate and extract the AVM. The algorithm takes a segmentation result as an input to perform AVM delineation. The algorithm determines the AVM region automatically, without any user interaction and independently of the segmentation algorithm used. The proposed approach is validated on brain blood vessel CTA images before and after embolization. The results obtained using the Dice coefficient comparisons, the volume percent error and the AVM center position show high accuracy of our method and indicate potentials for use in surgical planning.","PeriodicalId":424325,"journal":{"name":"Proceedings ELMAR-2014","volume":"250 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129078971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}