11,492 research outputs found
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Editorial -Special issue on adaptive multimedia computing
In recent years, there is an emerging research area in multimedia computing, with the increasing number of related work in scalable video, adaptive multimedia documents, adaptive multimedia services, to name just a few. This new trend comes about partly due to the increasing use of mobile media devices where media requirements could change among users and devices and at different times of reception or presentation, and partly due to the changing network conditions, where best-effort service is the general practice. Any change in Quality of Services (QoS) could imply a change in the delivery or scheduling of media contents. To complicate the matter, user interruptions or requirement changes during the communication process could also occur; for example, a user may not be satisfied with the current media quality and decide an upgrade in real time. The status quo is that this new research paradigm is beginning to take shape while no effort has been made to draw a roadmap for it. We could see some major research work missing, for example, formal methods or modeling of adaptive multimedi
Multimodal music information processing and retrieval: survey and future challenges
Towards improving the performance in various music information processing
tasks, recent studies exploit different modalities able to capture diverse
aspects of music. Such modalities include audio recordings, symbolic music
scores, mid-level representations, motion, and gestural data, video recordings,
editorial or cultural tags, lyrics and album cover arts. This paper critically
reviews the various approaches adopted in Music Information Processing and
Retrieval and highlights how multimodal algorithms can help Music Computing
applications. First, we categorize the related literature based on the
application they address. Subsequently, we analyze existing information fusion
approaches, and we conclude with the set of challenges that Music Information
Retrieval and Sound and Music Computing research communities should focus in
the next years
An Export Architecture for a Multimedia Authoring Environment
In this paper, we propose an export architecture that provides a clear
separation of authoring services from publication services. We illustrate this
architecture with the LimSee3 authoring tool and several standard publication
formats: Timesheets, SMIL, and XHTML
Exploration of audiovisual heritage using audio indexing technology
This paper discusses audio indexing tools that have been implemented for the disclosure of Dutch audiovisual cultural heritage collections. It explains the role of language models and their adaptation to historical settings and the adaptation of acoustic models for homogeneous audio collections. In addition to the benefits of cross-media linking, the requirements for successful tuning and improvement of available tools for indexing the heterogeneous A/V collections from the cultural heritage domain are reviewed. And finally the paper argues that research is needed to cope with the varying information needs for different types of users
A semantic event detection approach for soccer video based on perception concepts and finite state machines
A significant application area for automated video analysis technology is the generation of personalized highlights of sports events. Sports games are always composed of a range of significant events. Automatically detecting these events in a sports video can enable users to interactively select their own highlights. In this paper we propose a semantic event detection approach based on Perception Concepts and Finite State Machines to automatically detect significant events within soccer video. Firstly we define a Perception Concept set for soccer videos based on identifiable feature elements within a soccer video. Secondly we design PC-FSM models to describe semantic events in soccer videos. A particular strength of this approach is that users are able to design their own semantic events and transfer event detection into graph matching. Experimental results based on recorded soccer broadcasts are used to illustrate the potential of this approach
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A dynamic petri net model for iterative and interactive distributed multimedia presentation
Object Composition Petri Nets (OCPN), Priority Petri Nets (P-Net), Dynamic OCPN (DOCPN) and Enhanced P-Nets (EP-Net) have extended the original Petri Net to achieve the modeling of media synchronization and asynchronous user interactions during multimedia playback. Dynamic Petri Net (DPN) has been conceptualized to tackle existing problems in these two areas of modeling distributed multimedia systems. DPN features dynamic modeling elements which allows iteration and hence is able to reduce graph sizes of synchronous playback models while allowing greater details to be shown. DPN also introduces asynchronous event handling techniques that are powerful and effective. DPN was used in the design and modeling of a multimedia orchestration tool which is a typical representation of an application that works in a distributed multimedia system
A semantic content analysis model for sports video based on perception concepts and finite state machines
In automatic video content analysis domain, the key challenges are how to recognize important objects and how to model the spatiotemporal relationships between them. In this paper we propose a semantic content analysis model based on Perception Concepts (PCs) and Finite State Machines (FSMs) to automatically describe and detect significant semantic content within sports video. PCs are defined to represent important semantic patterns for sports videos based on identifiable feature elements. PC-FSM models are designed to describe spatiotemporal relationships between PCs. And graph matching method is used to detect high-level semantic automatically. A particular strength of this approach is that users are able to design their own highlights and transfer the detection problem into a graph matching problem. Experimental results are used to illustrate the potential of this approac
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