Information assimilation framework for event detection in multimedia surveillance systems

Most multimedia surveillance and monitoring systems nowadays utilize multiple types of sensors to detect events of interest as and when they occur in the environment. However, due to the asynchrony among and diversity of sensors, information assimilation – how to combine the information obtained from asynchronous and multifarious sources is an important and challenging research problem. In this paper, we propose a framework for information assimilation that addresses the issues – “when”, “what” and “how” to assimilate the information obtained from different media sources in order to detect events in multimedia surveillance systems. The proposed framework adopts a hierarchical probabilistic assimilation approach to detect atomic and compound events. To detect an event, our framework uses not only the media streams available at the current instant but it also utilizes their two important properties – first, accumulated past history of whether they have been providing concurring or contradictory evidences, and – second, the system designer’s confidence in them. The experimental results show the utility of the proposed framework.     

A framework for synchronous delivery of time-dependent multimedia data

Multimedia data often have time dependencies that must be satisfied at presentation time. To support a general purpose multimedia information system, these timing relationships must be managed to provide utility to both the data presentation system and the multimedia author. Timing management encompasses specification, data representation, temporal access control, playout scheduling, and run-time intermedia synchronization. In this paper we describe the components of our framework for supporting time-dependent multimedia data encompassing these areas and how they are assembled into a unified system.     

A backlight power management framework for battery-operated multimedia systems

Thin-film transistor liquid-crystal displays are systems widely used to support full-featured multimedia. For such systems, backlight is a major source of power dissipation. This article introduces a backlight power management framework and explores trade-offs in the extended dynamic-luminance-scaling design space in terms of energy reduction, performance penalty, and image quality.     

E-government multimedia big data platform for disaster management

Multimedia Tools and Applications - By efficiently managing and utilizing the city’s multimedia big data, 3D analysis and visualization of the city’s multimedia information can be...     

Machine learning based approach for multimedia surveillance during fire emergencies

Multimedia Tools and Applications - Video based surveillance of manmade disasters such as fire has become very hot topic in research and it is playing an important role in the development of smart...     

Web-based multimedia hand-therapy framework for measuring forward and inverse kinematic data

Multimedia Tools and Applications - Recognizing rotational and angular hand movements using a non-invasive way is a challenging task. In this paper, we present a web-based multimedia hand-Therapy...     

ConKMeL: a contextual knowledge management framework to support multimedia e-Learning

As the latest stage of learning and training evolution, e-Learning is supposed to provide intelligent functionalities not only in processing multi-media education resources but also in supporting context-sensitive pedagogical education processes. Towards providing an integrated solution for intelligent multimedia e-Learning, this paper presents a context-aware knowledge management framework named ConKMeL. Proposed framework features a semantic context-based approach for representing and integrating information and knowledge in e-Learning. Requirement analysis in university e-Learning environments shows that knowledge communications are usually in a hybrid mode across different conceptual levels. Based on the fact, a multi-layer contextual knowledge representation model called KG (knowledge graph) is presented. Corresponding key issues in development such as context-based knowledge retrieval and logical knowledge interpretation are discussed. On the application side, a scenario-based learning case study is shown to demonstrate the concepts and techniques developed in the ConKMeL framework.

A framework for user driven data management

Scientists within the materials engineering community produce a wide variety of data, with datasets differing in size and complexity. Examples include large 3D volume densitometry files (voxel) generated by microfocus computer tomography (μCT) and simple text files containing results from a tensile test. Increasingly, there is a need to share this data as part of international collaborations. The design of a suitable database schema and the architecture of a system that can cope with the varying information is a continuing problem in the management of heterogeneous data. We present a model flexible enough to meet users’ diverse requirements. Metadata is held using a database and its design allows users to control their own data structures. Data is held in a file store which, in combination with the metadata, gives huge flexibility. Using examples from materials engineering we illustrate how the model can be applied.     

Gaussian filter for TDOA based sound source localization in multimedia surveillance

Although multimedia surveillance systems are becoming increasingly ubiquitous in our living environment, automated multimedia surveillance systems based on video camera lacks the robustness and reliability most of the time in several real applications. To overcome this drawback, audio sensory devices have been taken into account in a considerable amount of research. For example, Sound Source Localization (SSL) may indicate potential security risks and could point the camera in that direction. In this paper, a reliable sound source localization based on Time-Difference-Of-Arrival (TDOA) is explored. The novel aspect of our approach includes a TDOA based Gaussian filter to improve the accuracy and stability of sound source localization. The advantage of our proposed algorithm is its extensive integration with various TDOA-based methods in all kinds of microphone array. The Experimental comparison shows significant improvement over the state of the art TDOA-based algorithm.

     

Context data management: an architectural framework for context-aware services

Mobile devices are equipped with increasing processing power and sensing capabilities, and mobile services can benefit from these features to provide a more personalized and context-aware experience to final users. To efficiently collect and deliver context information, a proper architecture is required, where heterogeneous context information can be processed to provide higher-level context information, context data are represented uniformly, and applications can process context data with high-level queries. This paper fulfils this goal of interoperability and domain independence by defining a framework for context data management relying on open standards (XMPP and REST), acting as an enabler for third-party context-aware applications; other main novelties of our work are the definition of a ContextML for standard context data representation, and a Context Query Language (CQL) to access context information based on high-level data filtering.     

Dynamic delegation framework for role based access control in distributed data management systems

This paper proposes a logic based framework that extends role based access control systems with dynamic delegation in a decentralised environment. It allows delegation of administrative privileges for both roles and access rights between roles. We have introduced the notion of trust in delegation and have shown how extended logic programs can be used to express and reason about roles and their delegations with trust degrees, roles’ privileges and their propagations, delegation depth as well as conflict resolution. Furthermore, our framework is able to enforce various role constraints such as separation of duties, role composition and cardinality constraints. The implementation of the framework is also discussed. The proposed framework is flexible and provides a sound basis for specifying and evaluating sophisticated role based access control policies in decentralised environments.     

CITIESData: a smart city data management framework

Smart city data come from heterogeneous sources including various types of the Internet of Things such as traffic, weather, pollution, noise, and portable devices. They are characterized with diverse quality issues and with different types of sensitive information. This makes data processing and publishing challenging. In this paper, we propose a framework to streamline smart city data management, including data collection, cleansing, anonymization, and publishing. The paper classifies smart city data in sensitive, quasi-sensitive, and open/public levels and then suggests different strategies to process and publish the data within these categories. The paper evaluates the framework using a real-world smart city data set, and the results verify its effectiveness and efficiency. The framework can be a generic solution to manage smart city data.     

Towards a framework for large-scale multimedia data storage and processing on Hadoop platform

Cloud computing techniques take the form of distributed computing by utilizing multiple computers to execute computing simultaneously on the service side. To process the increasing quantity of multimedia data, numerous large-scale multimedia data storage computing techniques in the cloud computing have been developed. Of all the techniques, Hadoop plays a key role in the cloud computing. Hadoop, a computing cluster formed by low-priced hardware, can conduct the parallel computing of petabytes of multimedia data. Hadoop features high-reliability, high-efficiency, and high-scalability. The numerous large-scale multimedia data computing techniques include not only the key core techniques, Hadoop and MapReduce, but also the data collection techniques, such as File Transfer Protocol and Flume. In addition, distributed system configuration allocation, automatic installation, and monitoring platform building and management techniques are all included. As a result, only with the integration of all the techniques, a reliable large-scale multimedia data platform can be offered. In this paper, we introduce how cloud computing can make a breakthrough by proposing a multimedia social network dataset on Hadoop platform and implementing a prototype version. Detailed specifications and design issues are discussed as well. An important finding of this article is that we can save more time if we conduct the multimedia social networking analysis using Cloud Hadoop Platform rather than using a single computer. The advantages of cloud computing over the traditional data processing practices are fully demonstrated in this article. The applicable framework designs and the tools available for the large-scale data processing are also proposed. We show the experimental multimedia data including data sizes and processing time.     

Tracking in multimedia data via robust reweighted local multi-task sparse representation for transportation surveillance

Multimedia Tools and Applications - It is of great importance in smart transportation surveillance to track object reliably from multimedia streaming data. Sparse representation based target...     

U-multimedia framework: a secure and intelligent multimedia service framework based on context information in U-home

In the last few years, intelligent secured multimedia services play a vital role along with ubiquitous home environment (Park et al. in Lecture Notes in Computer Science, vol. 4097, pp. 660–670, [2006]; Lecture Notes in Computer Science, vol. 4159, pp. 893–901, [2006]; IEICE Trans. Inf. Syst. E89-D(12):2831–2837, [2006]; Lecture Notes in Artificial Intelligence, vol. 4252, pp. 777–784, [2006]; Lecture Notes in Artificial Intelligence, vol. 3801, pp. 313–320, [2005]). There are certain constrains and limitations in providing effective and efficient services in U-home. The mechanism and applications are integrated to realize such services. Three different kinds of ubiquitous multimedia services are proposed in the framework. Based on the temporal and spatial context information, the surrounding situations are recognized. The contexts are collected and well analyzed with the preconditions to provide the final services. The proposed framework provides efficient services in the multimedia based deices based on the current context information.

Towards an ontology based framework for searching multimedia contents on the web

Multimedia Tools and Applications - We live in a world where there are huge number of consumers and producers of multimedia content. In this sea of information, finding the right content is like...