Abstracts


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Subspace Learning for Background Modeling: A Survey
Thierry Bouwmans

Background modeling is often used to detect moving object in video acquired by a fixed camera. Recently, subspace learning methods have been used to model the background in the idea to represent online data content while reducing dimension significantly. The first method using Principal Component Analysis (PCA) was proposed by Oliver et al. [1] and a representative patent using PCA concerns the detection of cars and persons in video surveillance [2]. Numerous improvements and variants were developed over the recent years. The purpose of this paper is to provide a survey and an original classification of these improvements. Firstly, we classify the improvements of the PCA in term of strategies and the variants in term of the used subspace learning algorithms. Then, we present a comparative evaluation of the variants and evaluate them with the state-of-art algorithms (SG, MOG, and KDE) by using the Wallflower dataset.

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Multimedia Tools for the Development of Algorithmic Thinking
Eva Milkova

The area of software development has undergone a rapid expansion and this trend is so far continuing. Each developer has to learn constantly and master new technology. However, the foundation a developer gains at the beginning of his/her career playing a crucial role. An essential part of studies at faculties preparing students in the area of computer science is the development of student's ability to think algorithmically. There are many different theoretical researches which deal with the question of how to consequently develop algorithmic thinking of students. Their basic aim is to improve the quality of teaching and students' self-learning. The aim of this paper is to introduce our approach that has proven to be successful in the optimization of teaching and learning a subject developing algorithmic thinking of beginners. This is followed by a discussion of the benefits of multimedia applications, explaining and visualizing the subject matter, testing the knowledge of students, and the recent key patents that have emerged in this field. A brief description of further deepening of algorithmic thinking within combinatorial optimization using appropriate multimedia support is given at the end of the paper.

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Multi-users quantum key distribution via wavelength routers in an optical network
Yupapin P. and Mitatha S.

We propose a new system of a continuous variable quantum key distribution via a wavelength router in the optical networks. A large bandwidth signal is generated by a soliton pulse propagating within the micro ring resonator, which is allowed to form the continuous wavelength with large tunable channel capacity. Two forms of soliton pulses are generated and localized, i.e. temporal and spatial solitons. The required information can be transmitted via the spatial soliton while the continuous variable quantum key distribution is formed by using the temporal one. This is formed by using an optical add/drop multiplexer incorporated in the optical network, where the localized soliton pulses are available for add/drop signals to/from the optical network. The high security and capacity information can be performed.

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A survey of peer- to -peer overlay schemes: Effectiveness, efficiency and security
Amoretti M.

In distributed computing, the peer-to-peer paradigm enables two or more entities to collaborate spontaneously in an overlay network of equals (peers) by using appropriate information and communication schemes without the necessity for central coordination. The key concept of the peer-to-peer paradigm is leveraging idle resources to do something useful, based on a collaborative approach. The increasing academic and industrial interest is resulting in the definition of standards and writing of patents.

In this paper we propose a categorization for the peer-to-peer overlay schemes and a survey of the most popular ones, comparing each other with respect to effectiveness and security. Most of them have been or are being used in content sharing systems, that over the last few years have enjoyed explosive popularity. Others are used in parallel and distributed computing, massively multi-player gaming, Internet streaming, ambient intelligence, etc. Considering such a wide range of applications, we discuss the importance of reputation management in supporting trust management among peer participants.

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Current issues and trends in wireless channel modeling and simulation
Baltzis K.B.

Wireless communication systems have witnessed tremendous growth over the last decades. However, the efficient and accurate characterization of the propagation channel still remains one of the most challenging and important issues in modern wireless communications. In order to meet the demands of a wide variety of applications, advanced propagation models that incorporate detailed representations of complicated propagation environments with sophisticated and efficient computational techniques are required. Moreover, the development of sophisticated models and methods increases as new applications emerge. This paper reviews current scientific and patent literature and discusses recent trends and future directions in the modeling and simulation of the wireless propagation medium. Within this context, several theoretical advances and underlying technologies used in the modeling and simulation of the radio channel are presented. A brief overview of current research trends in the capture and analysis of channel measurements and their application in channel modeling is also given.


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Three-dimensional spatial information systems: State of the art review
Schon B., Laefer D.F., Morrish S.W. and Bertolotto M.

A spatial information system (SIS) is critical to the hosting, querying, and analyzing of spatial data sets. The increasing availability of three-dimensional (3D) data (e.g. from aerial and terrestrial laser scanning) and the desire to use such data in large geo-spatial platforms have been dual drivers in the evolution of integrated SISs. Within this context, recent patents demonstrate efforts to handle large data sets, especially complex point clouds. While the development of feature-rich geo-systems has been well documented, the implementation of support for 3D capabilities is only now being addressed. This paper documents the underlying technologies implemented for the support for 3D features in SISs. Examples include ESRI's ArcGIS geo-database with its support for two-and-a-half dimensions (2.5D) in its Digital Elevation Model (DEM) and Triangular Irregular Network (TIN), the more recent development of the Terrain feature class, and support for 3D objects and buildings with its multi-patch feature class. Recent patents and research advances aim to extract DEMs and TINs automatically from point cloud data. In this context, various data structuring innovations are presented including both commercial and open source alternatives.


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A Robust ARX and ARMA Model order Estimation via Pivot-Neighbors Comparisons
Khaled E. Al-Qawasmi, Adnan M. Al-Smadi and Alaa Al-Hamami

Model order selection of an Autoregressive Moving Average (ARMA) process is an important problem. This paper presents a new algorithm for the estimation of an ARMA and autoregressive with exogenous input (ARX) model orders based on a rounding approach which uses the floor and the ceiling functions. The rounding approach is implemented to deal with the precision of binary words. The proposed algorithm is based on selecting a sequence of pivot cells from an MEV matrix which is based on the minimum eigenvalue of a covariance matrix computed from the observed data. It searches for the corner that contains the estimates of the true orders using the floor and the ceiling functions of the pivot cell values and the values of its neighbors. The proposed algorithm is an expansion of the algorithm proposed by Liang et al. (IEEE Transaction on Signal Processing, 1993; 41(10): 3003-3009). Recent patents and research advances aim to apply eigenvalue decomposition in estimation and prediction. Among the patents discussed is a method that describes estimation of uncertainty of a measuring machine where covariance matrix is subjected to eigenvalue decomposition.

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Implementations and Implications of Foveated Vision
Cornelius Weber and Jochen Triesch

Humans are equipped with ”space-variant“ vision, i.e. a concentration of photoreceptors, retinal ganglion cells and other visual resources at the central fovea, and a sparser coverage of other regions within a wide 180 degree field of view. If the entire visual field was equipped with foveal ganglion cell resolution, then the brain would have to cope with approximately 350 times more visual information.

We will review the relatively small number of existing hardware implementations and patents involving space variant vision. Space-variant vision is challenging to implement, because it comes along with distorted image representations, complicating standard geometry-based processing. Recent learning algorithms for feature detection and transformations are more flexible and may cope with foveated images.

Foveated vision requires an active vision system: ballistic eye-movements termed “saccades” frequently move the fovea to points of interest in the visual field. The metric of saccades is adjustable, and the resolution increase at the fovea may play a role in supplying the feedback to the system. Furthermore, saccades are related to visual space perception and embodied vision.

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Recent Patents on Genetic Programming
Michael O'Neill and Anthony Brabazon

Genetic Programming is a form of Natural Computing which adopts principles from neo-Darwinian evolution to automatically solve problems. It is a model induction method in that both the structure and parameters of the solution are explored simultaneously. Genetic Programming is a particularly interesting method as it is claimed to be an invention machine, producing solutions to problems that are competitive and in some cases superior to those produced by human experts. Its best solutions have become patentable inventions in their own right. In this article, we overview some of the recent patents relating to Genetic Programming over the past three years. In light of the number and diversity of patent applications during this period, it is clear that Genetic Programming is a vibrant field of research, which is having a significant impact on real-world applications, and is demonstrating clear commercial potential.