Search results for: Critical task method

Authors: Weizhi Xu, Zhiyong Liu, Dongrui Fan, Shuai Jiao, Xiaochun Ye, Fenglong Song, Chenggang Yan

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Many-core GPUs provide high computing ability and substantial bandwidth; however, optimizing irregular applications like SpMV on GPUs becomes a difficult but meaningful task. In this paper, we propose a novel method to improve the performance of SpMV on GPUs. A new storage format called HYB-R is proposed to exploit GPU architecture more efficiently. The COO portion of the matrix is partitioned recursively into a ELL portion and a COO portion in the process of creating HYB-R format to ensure that there are as many non-zeros as possible in ELL format. The method of partitioning the matrix is an important problem for HYB-R kernel, so we also try to tune the parameters to partition the matrix for higher performance. Experimental results show that our method can get better performance than the fastest kernel (HYB) in NVIDIA-s SpMV library with as high as 17% speedup.

Keywords: GPU, HYB-R, Many-core, Performance Tuning, SpMV

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Authors: Irene Rothe

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Object-oriented programming is a wonderful way to make programming of huge real life tasks much easier than by using procedural languages. In order to teach those ideas to students, it is important to find a good task that shows the advantages of OOprogramming very naturally. This paper gives an example, the game Battleship, which seems to work excellent for teaching the OO ideas (using Java, [1], [2], [3], [4]). A three-step task is presented for how to teach OO-programming using just one example suitable to convey many of the OO ideas. Observations are given at the end and conclusions about how the whole teaching course worked out.

Keywords: OO ideas, Java, teaching, engineering students.

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Authors: Fauzy M. Wan, Reem S.A. Baragash

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This study examined the effects of two dynamic visualizations on 60 Malaysian primary school student-s performance (time on task), retention and transference. The independent variables in this study were the two dynamic visualizations, the video and the animated instructions. The dependent variables were the gain score of performance, retention and transference. The results showed that the students in the animation group significantly outperformed the students in the video group in retention. There were no significant differences in terms of gain scores in the performance and transference among the animation and the video groups, although the scores were slightly higher in the animation group compared to the video group. The conclusion of this study is that the animation visualization is superior compared to the video in the retention for a procedural task.

Keywords: Dynamic visualization, Procedural Task, Retention, Transference

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Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

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Motion recognition from videos is actually a very complex task due to the high variability of motions. This paper describes the challenges of human motion recognition, especially motion representation step with relevant features. Our descriptor vector is inspired from Laban Movement Analysis method. We propose discriminative features using the Random Forest algorithm in order to remove redundant features and make learning algorithms operate faster and more effectively. We validate our method on MSRC-12 and UTKinect datasets.

Keywords: Human motion recognition, Discriminative LMA features, random forest, features reduction.

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Authors: Yasmeen Bassas, Sandra Kuebler, Allen Riddell

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Native Language Identification is one of the growing subfields in Natural Language Processing (NLP). The task of Native Language Identification (NLI) is mainly concerned with predicting the native language of an author’s writing in a second language. In this paper, we investigate the performance of two types of features; content-based features vs. content independent features when they are evaluated on a different corpus (using social media data “Reddit”). In this NLI task, the predefined models are trained on one corpus (TOEFL) and then the trained models are evaluated on a different data using an external corpus (Reddit). Three classifiers are used in this task; the baseline, linear SVM, and Logistic Regression. Results show that content-based features are more accurate and robust than content independent ones when tested within corpus and across corpus.

Keywords: NLI, NLP, content-based features, content independent features, social media corpus, ML.

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Authors: Steven Whittle, Ingrida Valiusaityte

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Within the domain of Systems Engineering the need to perform property aggregation to understand, analyze and manage complex systems is unequivocal. This can be seen in numerous domains such as capability analysis, Mission Essential Competencies (MEC) and Critical Design Features (CDF). Furthermore, the need to consider uncertainty propagation as well as the sensitivity of related properties within such analysis is equally as important when determining a set of critical properties within such a system. This paper describes this property breakdown in a number of domains within Systems Engineering and, within the area of CDFs, emphasizes the importance of uncertainty analysis. As part of this, a section of the paper describes possible techniques which may be used within uncertainty propagation and in conclusion an example is described utilizing one of the techniques for property and uncertainty aggregation within an aircraft system to aid the determination of Critical Design Features.

Keywords: Complex Systems, Critical Design Features, Property Aggregation, Uncertainty.

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Authors: T. Chandrasekhar, K. Thangavel, E. N. Sathishkumar

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Microarrays are made it possible to simultaneously monitor the expression profiles of thousands of genes under various experimental conditions. It is used to identify the co-expressed genes in specific cells or tissues that are actively used to make proteins. This method is used to analysis the gene expression, an important task in bioinformatics research. Cluster analysis of gene expression data has proved to be a useful tool for identifying co-expressed genes, biologically relevant groupings of genes and samples. In this work K-Means algorithms has been applied for clustering of Gene Expression Data. Further, rough set based Quick reduct algorithm has been applied for each cluster in order to select the most similar genes having high correlation. Then the ACV measure is used to evaluate the refined clusters and classification is used to evaluate the proposed method. They could identify compact clusters with feature selection method used to genes are selected.

Keywords: Clustering, Feature selection, Gene expression data, Quick reduct.

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Authors: Jan Zeman

Abstract:

The paper describes the futures trading and aims to design the speculators trading strategy. The problem is formulated as the decision making task and such as is solved. The solution of the task leads to complex mathematical problems and the approximations of the decision making is demanded. Two kind of approximation are used in the paper: Monte Carlo for the multi-step prediction and iteration spread in time for the optimization. The solution is applied to the real-market data and the results of the off-line experiments are presented.

Keywords: futures trading, decision making

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Authors: Samiah Alammari, Nassim Ammour

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When providing a massive number of tasks successively to a deep learning process, a good performance of the model requires preserving the previous tasks data to retrain the model for each upcoming classification. Otherwise, the model performs poorly due to the catastrophic forgetting phenomenon. To overcome this shortcoming, we developed a successful continual learning deep model for remote sensing hyperspectral image regions classification. The proposed neural network architecture encapsulates two trainable subnetworks. The first module adapts its weights by minimizing the discrimination error between the land-cover classes during the new task learning, and the second module tries to learn how to replicate the data of the previous tasks by discovering the latent data structure of the new task dataset. We conduct experiments on hyperspectral image (HSI) dataset on Indian Pines. The results confirm the capability of the proposed method.

Keywords: Continual learning, data reconstruction, remote sensing, hyperspectral image segmentation.

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Authors: A. Soria-Salinas, M.-P. Zorzano, J. Martín-Torres, J. Sánchez-García-Casarrubios, J.-L. Pérez-Díaz, A. Vakkada-Ramachandran

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The current state-of-the-art methods of mass gauging of Electric Propulsion (EP) propellants in microgravity conditions rely on external measurements that are taken at the surface of the tank. The tanks are operated under a constant thermal duty cycle to store the propellant within a pre-defined temperature and pressure range. We demonstrate using computational fluid dynamics (CFD) simulations that the heat-transfer within the pressurized propellant generates temperature and density anisotropies. This challenges the standard mass gauging methods that rely on the use of time changing skin-temperatures and pressures. We observe that the domes of the tanks are prone to be overheated, and that a long time after the heaters of the thermal cycle are switched off, the system reaches a quasi-equilibrium state with a more uniform density. We propose a new gauging method, which we call the Improved PVT method, based on universal physics and thermodynamics principles, existing TRL-9 technology and telemetry data. This method only uses as inputs the temperature and pressure readings of sensors externally attached to the tank. These sensors can operate during the nominal thermal duty cycle. The improved PVT method shows little sensitivity to the pressure sensor drifts which are critical towards the end-of-life of the missions, as well as little sensitivity to systematic temperature errors. The retrieval method has been validated experimentally with CO₂ in gas and fluid state in a chamber that operates up to 82 bar within a nominal thermal cycle of 38 °C to 42 °C. The mass gauging error is shown to be lower than 1% the mass at the beginning of life, assuming an initial tank load at 100 bar. In particular, for a pressure of about 70 bar, just below the critical pressure of CO₂, the error of the mass gauging in gas phase goes down to 0.1% and for 77 bar, just above the critical point, the error of the mass gauging of the liquid phase is 0.6% of initial tank load. This gauging method improves by a factor of 8 the accuracy of the standard PVT retrievals using look-up tables with tabulated data from the National Institute of Standards and Technology.

Keywords: Electric propulsion, mass gauging, propellant, PVT, xenon.

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Authors: Abolhassan Razminia, Mohammad-Ali Sadrnia

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One of the most attractive and important field of chaos theory is control of chaos. In this paper, we try to present a simple framework for chaotic motion control using the feedback linearization method. Using this approach, we derive a strategy, which can be easily applied to the other chaotic systems. This task presents two novel results: the desired periodic orbit need not be a solution of the original dynamics and the other is the robustness of response against parameter variations. The illustrated simulations show the ability of these. In addition, by a comparison between a conventional state feedback and our proposed method it is demonstrated that the introduced technique is more efficient.

Keywords: chaos, feedback linearization, robust control, periodic motion.

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Authors: Abhay Tawalare, Rajesh Lalwani

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An attempt in this paper proposes a re-modification to the minimum moment approach of resource leveling which is a modified minimum moment approach to the traditional method by Harris. The method is based on critical path method. The new approach suggests the difference between the methods in the selection criteria of activity which needs to be shifted for leveling resource histogram. In traditional method, the improvement factor found first to select the activity for each possible day of shifting. In modified method maximum value of the product of Resources Rate and Free Float was found first and improvement factor is then calculated for that activity which needs to be shifted. In the proposed method the activity to be selected first for shifting is based on the largest value of resource rate. The process is repeated for all the remaining activities for possible shifting to get updated histogram. The proposed method significantly reduces the number of iterations and is easier for manual computations.

Keywords: Re-Modified, Resource Leveling, Resources Rate, Free Float, Resource Histogram

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Authors: D. Sasikala, K. Premalatha

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The use of eXtensible Markup Language (XML) in web, business and scientific databases lead to the development of methods, techniques and systems to manage and analyze XML data. Semi-structured documents suffer due to its heterogeneity and dimensionality. XML structure and content mining represent convergence for research in semi-structured data and text mining. As the information available on the internet grows drastically, extracting knowledge from XML documents becomes a harder task. Certainly, documents are often so large that the data set returned as answer to a query may also be very big to convey the required information. To improve the query answering, a Semantic Tree Based Association Rule (STAR) mining method is proposed. This method provides intentional information by considering the structure, content and the semantics of the content. The method is applied on Reuter’s dataset and the results show that the proposed method outperforms well.

Keywords: Semi--structured Document, Tree based Association Rule (TAR), Semantic Association Rule Mining.

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Authors: Vahid Anari, Mina Bakhshi

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Visual search and identification of immunohistochemically stained tissue of meningioma was performed manually in pathologic laboratories to detect and diagnose the cancers type of meningioma. This task is very tedious and time-consuming. Moreover, because of cell's complex nature, it still remains a challenging task to segment cells from its background and analyze them automatically. In this paper, we develop and test a computerized scheme that can automatically identify cells in microscopic images of meningioma and classify them into positive (proliferative) and negative (normal) cells. Dataset including 150 images are used to test the scheme. The scheme uses Fuzzy C-means algorithm as a color clustering method based on perceptually uniform hue, saturation, value (HSV) color space. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images.

Keywords: Positive cell, color segmentation, HSV color space, immunohistochemistry, meningioma, thresholding, fuzzy c-means.

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Authors: Davod Khojasteh Salkuyeh

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An important task in solving second order linear ordinary differential equations by the finite difference is to choose a suitable stepsize h. In this paper, by using the stochastic arithmetic, the CESTAC method and the CADNA library we present a procedure to estimate the optimal stepsize hopt, the stepsize which minimizes the global error consisting of truncation and round-off error.

Keywords: Ordinary differential equations, optimal stepsize, error, stochastic arithmetic, CESTAC, CADNA.

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Authors: Shyh-Ming Chern

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Cubic equations of state (EoS), popular due to their simple mathematical form, ease of use, semi-theoretical nature and reasonable accuracy, are normally fitted to vapor-liquid equilibrium P-v-T data. As a result, they often show poor accuracy in the region near and above the critical point. In this study, the performance of the renowned Peng-Robinson (PR) and Patel-Teja (PT) EoS’s around the critical area has been examined against the P-v-T data of water. Both of them display large deviations at critical point. For instance, PR-EoS exhibits discrepancies as high as 47% for the specific volume, 28% for the enthalpy departure and 43% for the entropy departure at critical point. It is shown that incorporating P-v-T data of the supercritical region into the retuning of a cubic EoS can improve its performance at and above the critical point dramatically. Adopting a retuned acentric factor of 0.5491 instead of its genuine value of 0.344 for water in PR-EoS and a new F of 0.8854 instead of its original value of 0.6898 for water in PT-EoS reduces the discrepancies to about one third or less.

Keywords: Equation of state, EoS, supercritical water, SCW.

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Authors: Mikel Alonso López

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In order to begin the process of studying the task of making consumer decisions, the main decision models must be analyzed. The objective of this task is to see if there is a presence of emotions in those models, and analyze how authors that have created them consider their impact in consumer choices. In this paper, the most important models of consumer behavior are analysed. This review is useful to consider an unproblematic background knowledge in the literature. The order that has been established for this study is chronological.

Keywords: Consumer behaviour, emotions, decision making, consumer psychology.

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Authors: Maha ALjohani, James Blustein

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Communicating users' needs, goals and problems help designers and developers overcome challenges faced by end users. Personas are used to represent end users’ needs. In our research, creating personas allowed the following questions to be answered: Who are the potential user groups? What do they want to achieve by using the service? What are the problems that users face? What should the service provide to them? To develop realistic personas, we conducted a focus group discussion with undergraduate and graduate students and also interviewed a university librarian. The personas were created to help evaluating the Institutional Repository that is based on the DSpace system. The profiles helped to communicate users' needs, abilities, tasks, and problems, and the task scenarios used in the heuristic evaluation were based on these personas. Four personas resulted of a focus group discussion with undergraduate and graduate students and from interviewing a university librarian. We then used these personas to create focused task-scenarios for a heuristic evaluation on the system interface to ensure that it met users' needs, goals, problems and desires. In this paper, we present the process that we used to create the personas that led to devise the task scenarios used in the heuristic evaluation as a follow up study of the DSpace university repository.

Keywords: Heuristic Evaluation, Institutional Repositories, User Experience, Human Computer Interaction, User Profiles, Personas, Task Scenarios, Heuristics.

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Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, capsule network, capacity optimization, character recognition, data augmentation; semantic segmentation.

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Authors: Thiago M. R Dias, Gray F. Moita

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The analysis of scientific collaboration networks has contributed significantly to improving the understanding of how does the process of collaboration between researchers and also to understand how the evolution of scientific production of researchers or research groups occurs. However, the identification of collaborations in large scientific databases is not a trivial task given the high computational cost of the methods commonly used. This paper proposes a method for identifying collaboration in large data base of curriculum researchers. The proposed method has low computational cost with satisfactory results, proving to be an interesting alternative for the modeling and characterization of large scientific collaboration networks.

Keywords: Extraction and data integration, Information Retrieval, Scientific Collaboration.

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Authors: Mourad Ykhlef, Hebah ElGibreen

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Mining Sequential Patterns in large databases has become an important data mining task with broad applications. It is an important task in data mining field, which describes potential sequenced relationships among items in a database. There are many different algorithms introduced for this task. Conventional algorithms can find the exact optimal Sequential Pattern rule but it takes a long time, particularly when they are applied on large databases. Nowadays, some evolutionary algorithms, such as Particle Swarm Optimization and Genetic Algorithm, were proposed and have been applied to solve this problem. This paper will introduce a new kind of hybrid evolutionary algorithm that combines Genetic Algorithm (GA) with Particle Swarm Optimization (PSO) to mine Sequential Pattern, in order to improve the speed of evolutionary algorithms convergence. This algorithm is referred to as SP-GAPSO.

Keywords: Genetic Algorithm, Hybrid Evolutionary Algorithm, Particle Swarm Optimization algorithm, Sequential Pattern mining.

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Authors: Li Chen, ZhouLong Li, Qing-zhen Bi, LiMin Zhu

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A new tool path planning method for 5-axis flank milling of a globoidal indexing cam is developed in this paper. The globoidal indexing cam is a practical transmission mechanism due to its high transmission speed, accuracy and dynamic performance. Machining the cam profile is a complex and precise task. The profile surface of the globoidal cam is generated by the conjugate contact motion of the roller. The generated complex profile surface is usually machined by 5-axis point-milling method. The point-milling method is time-consuming compared with flank milling. The tool path for 5-axis flank milling of globoidal cam is developed to improve the cutting efficiency. The flank milling tool path is globally optimized according to the minimum zone criterion, and high accuracy is guaranteed. The computational example and cutting simulation finally validate the developed method.

Keywords: Globoidal cam, flank milling, LSQR, MINIMAX.

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Authors: M. Ovinis, D. Kerr, K. Bouazza-Marouf, M. Vloeberghs

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In this paper, the feasibility of using machine vision to assess task completion in a surgical intervention is investigated, with the aim of incorporating vision based inspection in robotic surgery systems. The visually rich operative field presents a good environment for the development of automated visual inspection techniques in these systems, for a more comprehensive approach when performing a surgical task. As a proof of concept, machine vision techniques were used to distinguish the two possible outcomes i.e. satisfactory or unsatisfactory, of three primary surgical tasks involved in creating a burr hole in the skull, namely incision, retraction, and drilling. Encouraging results were obtained for the three tasks under consideration, which has been demonstrated by experiments on cadaveric pig heads. These findings are suggestive for the potential use of machine vision to validate successful task completion in robotic surgery systems. Finally, the potential of using machine vision in the operating theatre, and the challenges that must be addressed, are identified and discussed.

Keywords: Machine vision, robotic surgery, visual inspection.

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Authors: Joseph Oh, Bo-Hyun Kim, Jae-Yong Baek

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This study suggests how an order-receiving company can avoid disclosing schedule information on unit tasks to the order-placing company when carrying out a collaborative project on the value chain in an order-oriented industry. Specifically, it suggests methods for keeping schedule information confidential, and categorizes potential situations by inter-task dependency. Lastly, an approach to select the most optimal non-disclosure method is discussed. With the methods for not disclosing work-related information suggested in the study, order-receiving companies can logically deal with political issues relating to the question of whether or not to disclose information upon the execution of a collaborative project in cooperation with an order-placing firm. Moreover, order-placing companies can monitor undistorted information, while respecting the legitimate rights of an order-receiving company. Therefore, it is fair to say that the suggestions made in this study will contribute to the smooth operation of collaborative intercompany projects.

Keywords: collaborative project, dependency, schedule management, unit task.

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Authors: Beste Kaysı, Yasemin Topaloğlu

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Usability is one of the most important quality attributes for web-based information systems. Specifically, for e-commerce applications, usability becomes more prominent. In this study, we aimed to explore the features that experienced users seek in e-commerce applications. We used eye tracking method in evaluations. Eye movement data are obtained from the eye-tracking method and analyzed based on task completion time, number of fixations, as well as heat map and gaze plot measures. The results of the analysis show that the eye movements of participants' are too static in certain areas and their areas of interest are scattered in many different places. It has been determined that this causes users to fail to complete their transactions. According to the findings, we outlined the issues to improve the usability of e-commerce websites. Then we propose solutions to identify the issues. In this way, it is expected that e-commerce sites will be developed which will make experienced users more satisfied.

Keywords: E-commerce websites, eye tracking method, usability, website evaluations.

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Authors: B. G. Sheeparamatti, Prashant Hanasi, Vanita Abbigeri

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The objective of this work is to carryout critical comparison of different actuation mechanisms like electrostatic, thermal, piezoelectric, and magnetic with reference to a micro cantilever. The relevant parameters like force generated, displacement are compared in actuation methods. With these results, helps in choosing the best actuation method for a particular application. In this study, Comsol/Multiphysics software is used. Modeling and simulation is done by considering the micro cantilever of same dimensions as an actuator using all the above mentioned actuation techniques. In addition to their small size, micro actuators consume very little power and are capable of accurate results. In this work, a comparison of actuation mechanisms is done to decide the efficient system in micro domain.

Keywords: Actuation techniques, microswitch, micro actuator, microsystems.

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Authors: Olimpia Matarazzo, Fabrizio Ferrara

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In two studies we tested the hypothesis that the appropriate linguistic formulation of a deontic rule – i.e. the formulation which clarifies the monadic nature of deontic operators - should produce more correct responses than the conditional formulation in Wason selection task. We tested this assumption by presenting a prescription rule and a prohibition rule in conditional vs. proper deontic formulation. We contrasted this hypothesis with two other hypotheses derived from social contract theory and relevance theory. According to the first theory, a deontic rule expressed in terms of cost-benefit should elicit a cheater detection module, sensible to mental states attributions and thus able to discriminate intentional rule violations from accidental rule violations. We tested this prevision by distinguishing the two types of violations. According to relevance theory, performance in selection task should improve by increasing cognitive effect and decreasing cognitive effort. We tested this prevision by focusing experimental instructions on the rule vs. the action covered by the rule. In study 1, in which 480 undergraduates participated, we tested these predictions through a 2 x 2 x 2 x 2 (type of the rule x rule formulation x type of violation x experimental instructions) between-subjects design. In study 2 – carried out by means of a 2 x 2 (rule formulation x type of violation) between-subjects design - we retested the hypothesis of rule formulation vs. the cheaterdetection hypothesis through a new version of selection task in which intentional vs. accidental rule violations were better discriminated. 240 undergraduates participated in this study. Results corroborate our hypothesis and challenge the contrasting assumptions. However, they show that the conditional formulation of deontic rules produces a lower performance than what is reported in literature.

Keywords: Deontic reasoning; Evolutionary, linguistic, logical, pragmatic factors; Wason selection task

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Authors: Ahmed Shinkafi, Craig Lawson

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There is a great advancement towards the All-Electric Aircraft (AEA) technology. The AEA concept assumes that all aircraft systems will be integrated into one electrical power source in the future. The principle of the electro-thermal system is to transfer the energy required for anti/de-icing to the protected areas in electrical form. However, powering a large aircraft anti-icing system electrically could be quite excessive in cost and system weight. Hence, maximising the anti/de-icing efficiency of the electro-thermal system in order to minimise its power demand has become crucial to electro-thermal de-icing system sizing. In this work, an enhanced methodology has been developed for conceptual sizing of aircraft electro-thermal de-icing System. The work factored those critical terms overlooked in previous studies which were critical to de-icing energy consumption. A case study of a typical large aircraft wing de-icing was used to test and validate the model. The model was used to optimise the system performance by a trade-off between the de-icing peak power and system energy consumption. The optimum melting surface temperatures and energy flux predicted enabled the reduction in the power required for de-icing. The weight penalty associated with electro-thermal anti-icing/de-icing method could be eliminated using this method without under estimating the de-icing power requirement.

Keywords: Aircraft de-icing system, electro-thermal, in-flight icing.

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Authors: Jae Kyung Son, Wan Shik Jang, Sung hyun Shim, Yoon Gyung Sung

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This paper is concerned with the application of the vision control algorithm for robot's point placement task in discontinuous trajectory caused by obstacle. The presented vision control algorithm consists of four models, which are the robot kinematic model, vision system model, parameters estimation model, and robot joint angle estimation model.When the robot moves toward a target along discontinuous trajectory, several types of obstacles appear in two obstacle regions. Then, this study is to investigate how these changes will affect the presented vision control algorithm.Thus, the practicality of the vision control algorithm is demonstrated experimentally by performing the robot's point placement task in discontinuous trajectory by obstacle.

Keywords: Vision control algorithm, location of obstacle region, range of obstacle region, point placement.

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Authors: C. Lodato, S. Lopes

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This paper describes a segmentation algorithm based on the cooperation of an optical flow estimation method with edge detection and region growing procedures. The proposed method has been developed as a pre-processing stage to be used in methodologies and tools for video/image indexing and retrieval by content. The addressed problem consists in extracting whole objects from background for producing images of single complete objects from videos or photos. The extracted images are used for calculating the object visual features necessary for both indexing and retrieval processes. The first task of the algorithm exploits the cues from motion analysis for moving area detection. Objects and background are then refined using respectively edge detection and region growing procedures. These tasks are iteratively performed until objects and background are completely resolved. The developed method has been applied to a variety of indoor and outdoor scenes where objects of different type and shape are represented on variously textured background.

Keywords: Motion Detection, Object Extraction, Optical Flow, Segmentation.

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