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Dive into the research topics where Kosmas Dimitropoulos is active.

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Featured researches published by Kosmas Dimitropoulos.


Digital Signal Processing | 2013

Video fire detection - Review

A. Enis Cetin; Kosmas Dimitropoulos; Benedict Gouverneur; Nikos Grammalidis; Osman Günay; Y. Hakan Habiboglu; B. Ugur Toreyin; Steven Verstockt

This is a review article describing the recent developments in Video based Fire Detection (VFD). Video surveillance cameras and computer vision methods are widely used in many security applications. It is also possible to use security cameras and special purpose infrared surveillance cameras for fire detection. This requires intelligent video processing techniques for detection and analysis of uncontrolled fire behavior. VFD may help reduce the detection time compared to the currently available sensors in both indoors and outdoors because cameras can monitor volumes and do not have transport delay that the traditional point sensors suffer from. It is possible to cover an area of 100 km^2 using a single pan-tilt-zoom camera placed on a hilltop for wildfire detection. Another benefit of the VFD systems is that they can provide crucial information about the size and growth of the fire, direction of smoke propagation.


Signal Processing, Pattern Recognition and Applications / 779: Computer Graphics and Imaging | 2012

Flame Detection for Video-based Early Fire Warning Systems and 3D Visualization of Fire Propagation

Kosmas Dimitropoulos; Filareti Tsalakanidou; Nikos Grammalidis

Early and accurate detection and localization of flame is an essential requirement of modern early fire warning systems. Video-based systems can be used for this purpose; however, flame detection remains a challenging issue due to the fact that many natural objects have similar characteristics with fire. In this paper, we present a new algorithm for video based flame detection, which employs various spatio-temporal features such as colour probability, contour irregularity, spatial energy, flickering and spatio-temporal energy. Various background subtraction algorithms are tested and comparative results in terms of computational efficiency and accuracy are presented. Experimental results with two classification methods show that the proposed methodology provides high fire detection rates with a reasonable false alarm ratio. Finally, a 3D visualization tool for the estimation of the fire propagation is outlined and simulation results are presented and discussed.


Third International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2015) | 2015

Selective 4D modelling framework for spatial-temporal land information management system

Anastasios D. Doulamis; Sofia Soile; Nikolaos D. Doulamis; Christina Chrisouli; Nikos Grammalidis; Kosmas Dimitropoulos; Charalambos Manesis; Chryssy Potsiou; Charalabos Ioannidis

This paper introduces a predictive (selective) 4D modelling framework where only the spatial 3D differences are modelled at the forthcoming time instances, while regions of no significant spatial-temporal alterations remain intact. To accomplish this, initially spatial-temporal analysis is applied between 3D digital models captured at different time instances. So, the creation of dynamic change history maps is made. Change history maps indicate spatial probabilities of regions needed further 3D modelling at forthcoming instances. Thus, change history maps are good examples for a predictive assessment, that is, to localize surfaces within the objects where a high accuracy reconstruction process needs to be activated at the forthcoming time instances. The proposed 4D Land Information Management System (LIMS) is implemented using open interoperable standards based on the CityGML framework. CityGML allows the description of the semantic metadata information and the rights of the land resources. Visualization aspects are also supported to allow easy manipulation, interaction and representation of the 4D LIMS digital parcels and the respective semantic information. The open source 3DCityDB incorporating a PostgreSQL geo-database is used to manage and manipulate 3D data and their semantics. An application is made to detect the change through time of a 3D block of plots in an urban area of Athens, Greece. Starting with an accurate 3D model of the buildings in 1983, a change history map is created using automated dense image matching on aerial photos of 2010. For both time instances meshes are created and through their comparison the changes are detected.


international conference on progress in cultural heritage preservation | 2012

Flame detection for video-based early fire warning for the protection of cultural heritage

Kosmas Dimitropoulos; Osman Günay; Kivanc Kose; Fatih Erden; F. Chaabene; Filareti Tsalakanidou; Nikolaos Grammalidis; A. Enis Cetin

Cultural heritage and archaeological sites are exposed to the risk of fire and early warning is the only way to avoid losses and damages. The use of terrestrial systems, typically based on video cameras, is currently the most promising solution for advanced automatic wildfire surveillance and monitoring. Video cameras are sensitive in visible spectra and can be used either for flame or smoke detection. This paper presents and compares three video-based flame detection techniques, which were developed within the FIRESENSE EU research project.


advanced video and signal based surveillance | 2013

Real time video fire detection using spatio-temporal consistency energy

Panagiotis Barmpoutis; Kosmas Dimitropoulos; Nikos Grammalidis

In this paper a new algorithm is proposed for detecting fire from video data in real time based on a combination of features, including a new spatio-temporal consistency feature. A significant challenge in flame detection systems is to discriminate between actual fire and false alarms caused by fire colored objects. Towards this aim, we propose an algorithm that has significant advantages: a) it is fast since rectangular non-overlapping blocks are used as basic elements (instead of arbitrary-shaped regions) b) a spatio-temporal consistency feature is used in addition to color probability, spatial energy, flickering and spatio-temporal energy features and c) an improved rule-based classification approach is proposed, after evaluating seven different classification approaches. Experimental results are presented that confirm the efficiency of the proposed approach.


2015 Digital Heritage | 2015

Designing Serious Games for ICH education.

Francesca Maria Dagnino; Francesca Pozzi; Erdal Yilmaz; Nikos Grammalidis; Kosmas Dimitropoulos; Filareti Tsalakanidou

The paper presents the experience matured in the i-Treasures project, in which 3D game-like applications were designed and developed with the aim of providing innovative tools for Intangible Cultural Heritage (ICH) education. The decision to develop Serious Games grounded on the specific learning needs linked to the nature of the ICH considered (dances, craftsmanship, singing expressions, etc.) and to the benefits that the research in Games Based Learning has pointed out regarding the use of games with educational purposes. In the paper, the i-Treasures game-like applications are described, with particular attention to the design and developmental process that was carried out with the involvement of a multidisciplinary team. In the game development, a huge effort was put into making the most of the benefits of games; these aspects will be discussed and highlighted. The difficulties met will be discussed as well, so as to provide a clear idea about the process and the issues encountered.


Special Session on RBG and Spectral Imaging for Civil/Survey Engineering, Cultural, Environmental, Industrial Applications | 2016

Extracting Dynamics from Multi-dimensional Time-evolving Data using a Bag of Higher-order Linear Dynamical Systems

Kosmas Dimitropoulos; Panagiotis Barmpoutis; Alexandors Kitsikidis; Nikos Grammalidis

In this paper we address the problem of extracting dynamics from multi-dimensional time-evolving data. To this end, we propose a linear dynamical model (LDS), which is based on the higher order decomposition of the observation data. In this way, we are able to extract a new descriptor for analyzing data of multiple elements coming from of the same or different data sources. Each sequence of data is modeled as a collection of higher order LDS descriptors (h-LDSs), which are estimated in equally sized temporal segments of data. Finally, each sequence is represented as a term frequency histogram following a bag-ofsystems approach, in which h-LDSs are used as feature descriptors. For evaluating the performance of the proposed methodology to extract dynamics from time evolving multidimensional data and using them for classification purposes in various applications, in this paper we consider two different cases: dynamic texture analysis and human motion recognition. Experimental results with two datasets for dynamic texture analysis and two datasets for human action recognition demonstrate the great potential of the proposed


2017 9th International Conference on Virtual Worlds and Games for Serious Applications (VS-Games) | 2017

An adaptive framework for the creation of bodymotion-based games

Athina Grammatikopoulou; Sohaib Laraba; Ozan Sahbenderoglu; Kosmas Dimitropoulos; Nikos Grammalidis

As of the early 20th century, a significant body of research has been published that shows how effective game-based learning and gamification techniques can be compared to other methods. However, creating games can be time consuming and usually demands a significant effort. Therefore, this paper focuses on the design and development of a novel framework for the rapid design of body-motion-based customizable game-like applications. This framework consists of two components: i) an interface that allows the user to design the game and capture the motion data, and ii) a customizable game for learning and training using off-the-shelf motion capture sensors like the Microsoft Kinect. The game is automatically configured based on the output of the game design interface. In order to evaluate the proposed system, a pilot use case for the Latin dance Salsa has been selected. Preliminary small-scaled experiments with latin dance students have shown the great potential of the proposed application.


Archive | 2016

Classification of Nuclei in Follicular Lyphoma Tissue Sections Using Different Stains and Bayesian Networks

Kosmas Dimitropoulos; Panagiotis Barmpoutis; Triantafyllia Koletsa; Ioannis Kostopoulos; Nikos Grammalidis

Automated centroblast (CB) detection in Follicular Lymphoma (FL) tissue samples has recently attracted significant research interest. Most of the methods described in the literature are based on the use of Hematoxilin and Eosin (H&E) stain. However, the automated detection of CBs from H&E stained images remains a challenging issue. To this end, this paper presents a novel approach which is based on the use of both PAX5 and H&E stains in tissue sections sliced at the thickness of 1μm. The goal of PAX5 is three-fold: to facilitate the segmentation of nuclei, to remove a number of follicular dendritic cells and finally to extract morphological characteristics of nuclei. Furthermore, the use of H&E stain enables us to extract textural information related to histological characteristics used by pathologists in diagnosis of FL grading. In our method we propose a novel algorithm for the separation of overlapped nuclei inspired by the clustering of large scale visual vocabularies. Finally, aiming to model pathologists’ knowledge used in FL grading, we use a Bayesian Network classifier to combine the morphological and textural characteristics. Experiments conducted on a dataset of ten pairs of PAX5 and H&E images demonstrate the potential of the proposed approach providing an average detection rate of 93.46%.


Mixed Reality and Gamification for Cultural Heritage | 2017

Intangible Cultural Heritage and New Technologies: Challenges and Opportunities for Cultural Preservation and Development

Marilena Alivizatou-Barakou; Alexandros Kitsikidis; Filareti Tsalakanidou; Kosmas Dimitropoulos; Chantas Giannis; Spiros Nikolopoulos; Samer Al Kork; Bruce Denby; Lise Crevier Buchman; Martine Adda-Decker; Claire Pillot-Loiseau; Joëlle Tillmane; Stéphane Dupont; Benjamin Picart; Francesca Pozzi; Michela Ott; Yilmaz Erdal; Vasileios Charisis; Stelios Hadjidimitriou; Marius Cotescu; Christina Volioti; Athanasios Manitsaris; Sotiris Manitsaris; Nikos Grammalidis

Intangible cultural heritage (ICH) is a relatively recent term coined to represent living cultural expressions and practices, which are recognised by communities as distinct aspects of identity. The safeguarding of ICH has become a topic of international concern primarily through the work of United Nations Educational, Scientific and Cultural Organization (UNESCO). However, little research has been done on the role of new technologies in the preservation and transmission of intangible heritage. This chapter examines resources, projects and technologies providing access to ICH and identifies gaps and constraints. It draws on research conducted within the scope of the collaborative research project, i-Treasures. In doing so, it covers the state of the art in technologies that could be employed for access, capture and analysis of ICH in order to highlight how specific new technologies can contribute to the transmission and safeguarding of ICH.

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Nikos Grammalidis

Aristotle University of Thessaloniki

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Filareti Tsalakanidou

Aristotle University of Thessaloniki

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Francesca Pozzi

National Research Council

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Nikos Grammalidis

Aristotle University of Thessaloniki

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Panagiotis Barmpoutis

Information Technology Institute

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Vasileios Charisis

Aristotle University of Thessaloniki

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Benedict Gouverneur

Katholieke Universiteit Leuven

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