Human action annotation,modeling and analysis based on implicit user interaction

This paper proposes an integrated framework for analyzing human actions in video streams. Despite most current approaches that are just based on automatic spatiotemporal analysis of sequences, the proposed method introduces the implicit user-in-the-loop concept for dynamically mining semantics and annotating video streams. This work sets a new and ambitious goal: to recognize, model and properly use “average user’s” selections, preferences and perception, for dynamically extracting content semantics. The proposed approach is expected to add significant value to hundreds of billions of non-annotated or inadequately annotated video streams existing in the Web, file servers, databases etc. Furthermore expert annotators can gain important knowledge relevant to user preferences, selections, styles of searching and perception.     

Singular PDEs and the assignment of zero dynamics in nonlinear systems

The present research work aims at the development of a systematic method to arbitrarily assign the zero dynamics of a nonlinear system by constructing the requisite synthetic output maps. The minimum-phase synthetic output maps constructed can be made statically equivalent to the original output maps, and therefore, they could be directly used for nonminimum-phase compensation purposes. Specifically, the mathematical formulation of the problem is realized via a system of first-order nonlinear singular PDEs and a rather general set of necessary and sufficient conditions for solvability is derived. The solution to the above system of singular PDEs can be proven to be locally analytic and this enables the development of a series solution method that is easily programmable with the aid of a symbolic software package. The minimum-phase synthetic output maps that induce the prescribed zero dynamics for the original nonlinear system can be computed on the basis of the solution of the aforementioned system of singular PDEs. Moreover, static equivalence to the original output map can be readily established by a simple algebraic construction.     

Identification of Move Method Refactoring Opportunities

Placement of attributes/methods within classes in an object-oriented system is usually guided by conceptual criteria and aided by appropriate metrics. Moving state and behavior between classes can help reduce coupling and increase cohesion, but it is nontrivial to identify where such refactorings should be applied. In this paper, we propose a methodology for the identification of Move Method refactoring opportunities that constitute a way for solving many common Feature Envy bad smells. An algorithm that employs the notion of distance between system entities (attributes/methods) and classes extracts a list of behavior-preserving refactorings based on the examination of a set of preconditions. In practice, a software system may exhibit such problems in many different places. Therefore, our approach measures the effect of all refactoring suggestions based on a novel Entity Placement metric that quantifies how well entities have been placed in system classes. The proposed methodology can be regarded as a semi-automatic approach since the designer will eventually decide whether a suggested refactoring should be applied or not based on conceptual or other design quality criteria. The evaluation of the proposed approach has been performed considering qualitative, metric, conceptual, and efficiency aspects of the suggested refactorings in a number of open-source projects.     

A top-down event-driven approach for concurrent activity recognition

In this paper a framework for automatic online workflow recognition in industrial environments where the issue of concurrent activities rises, is presented. The framework consists of three main parts: The first part is devoted to detecting activity in specific Regions of Interest (ROIs) of the video sequence. This is effected by separating each frame into ROIs and representing the resulting subimages through feature vectors. By observing these vectors we can determine when there is action in a particular ROI. The second part of the framework lies in examining whether the detected activity corresponds to a workflow related event. This is accomplished by HMM modeling. Finally, the third part employs a string matching based technique to confirm the validity of the observed sequence of events or correct any detection or classification errors. This last step also addresses a top down approach by informing lower system levels (such as image representation or object tracking) about the errors committed. The performance of the proposed approach is thoroughly evaluated under real-life complex visual workflow understanding scenarios, in an industrial plant. The obtained results are compared and discussed.     

Building highly realistic facial modeling and animation: a survey

This paper provides a comprehensive survey on the techniques for human facial modeling and animation. The survey is carried out from two different perspectives: facial modeling, which concerns how to produce 3D face models, and facial animation, which regards how to synthesize dynamic facial expressions. To generate an individual face model, we can either perform individualization of a generic model or combine face models from an existing face collection. With respect to facial animation, we have further categorized the techniques into simulation-based, performance-driven and shape blend-based approaches. The strength and weakness of these techniques within each category are discussed, alongside with the applications of these techniques to various exploitations. In addition, a brief historical review of the technique evolution is provided. Limitations and future trend are discussed. Conclusions are drawn at the end of the paper.     

A non-linear index to evaluate a journal’s scientific impact

The purpose of this study is to define a bibliometric indicator of the scientific impact of a journal, which combines objectivity with the ability to bridge many different bibliometric factors and in particular the side factors presented along with celebrated ISI impact factor. The particular goal is to determine a standard threshold value in which an independent self-organizing system will decide the correlation between this value and the impact factor of a journal. We name this factor “Cited Distance Factor (CDF)” and it is extracted via a well-fitted, recurrent Elman neural network. For a case study of this implementation we used a dataset of all journals of cell biology, ranking them according to the impact factor from the Web of Science Database and then comparing the rank according to the cited distance. For clarity reasons we also compare the cited distance factor with already known measures and especially with the recently introduced eigenfactor of the institute of scientific information (ISI).     

A context-aware middleware for real-time semantic enrichment of distributed multimedia metadata

This paper investigates the problem of the real-time integration and processing of multimedia metadata collected by a distributed sensor network. The discussed practical problem is the efficiency of the technologies used in creating a Knowledge Base in real-time. Specifically, an approach is proposed for the real-time, rule-based semantic enrichment of lower level context features with higher-level semantics. The distinguishing characteristic is the provision of an intelligent middleware-based architecture on which low level components such as sensors, feature extraction algorithms, data sources, and high level components such as application-specific ontologies can be plugged. Throughout the paper, Priamos, a middleware architecture based on Semantic Web technologies is presented, together with a stress-test of the system’s operation under two test case scenarios: A smart security surveillance application and a smart meeting room application. Performance measurements are conducted and corresponding results are exposed.     

Dependency modelling for inconsistency management in Digital Preservation – The PERICLES approach

The rise of the Semantic Web has provided cultural heritage researchers and practitioners with several tools for providing semantically rich representations and interoperability of cultural heritage collections. Although indeed offering a lot of advantages, these tools, which come mostly in the form of ontologies and related vocabularies, do not provide a conceptual model for capturing contextual and environmental dependencies, contributing to long-term digital preservation. This paper presents one of the key outcomes of the PERICLES FP7 project, the Linked Resource Model, for modelling dependencies as a set of evolving linked resources. The adoption of the proposed model and the consistency of its representation are evaluated via a specific instantiation involving the domain of digital video art.     

MITIS: a WWW-based medical system for managing and processing gynecological-obstetrical-radiological data

In this paper a World Wide Web (WWW)-based medical system, called MITIS, is designed and developed for the management and processing of obstetrical, gynecological and radiological medical data. The system records all the necessary medical information in terms of patient data, examinations, and operations and provides the user-expert with advanced image processing tools for the manipulation, processing and storage of ultrasound and mammographic images. The system can be installed in a hospital's Local Area Network (LAN) where it can access picture archival and communication systems (PACS) servers (if available), or any other server within the radiology department, for image archiving and retrieval, based on the digital imaging and communication in medicine (DICOM) 3.0 protocol, over TCP/IP and also it is accessible to external physicians via the hospital's Internet connection. MITIS is composed as a set of independent WWW modules (ISAPI server extension dlls) and a Win32 application (COM+ server) for mammography image processing and evaluation.