145,007 research outputs found
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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
Measuring concept similarities in multimedia ontologies: analysis and evaluations
The recent development of large-scale multimedia concept ontologies has provided a new momentum for research in the semantic analysis of multimedia repositories. Different methods for generic concept detection have been extensively studied, but the question of how to exploit the structure of a multimedia ontology and existing inter-concept relations has not received similar attention. In this paper, we present a clustering-based method for modeling semantic concepts on low-level feature spaces and study the evaluation of the quality of such models with entropy-based methods. We cover a variety of methods for assessing the similarity of different concepts in a multimedia ontology. We study three ontologies and apply the proposed techniques in experiments involving the visual and semantic similarities, manual annotation of video, and concept detection. The results show that modeling inter-concept relations can provide a promising resource for many different application areas in semantic multimedia processing
A Motion-Driven Approach for Fine-Grained Temporal Segmentation of User-Generated Videos
This paper presents an algorithm for the temporal segmentation of user-generated videos into visually coherent parts that correspond to individual video capturing activities. The latter include camera pan and tilt, change in focal length and camera displacement. The proposed approach identifies the aforementioned activities by extracting and evaluating the region-level spatio-temporal distribution of the optical flow over sequences of neighbouring video frames. The performance of the algorithm was evaluated with the help of a newly constructed ground-truth dataset, against several state-of-the-art techniques and variations of them. Extensive evaluation indicates the competitiveness of the proposed approach in terms of detection accuracy, and highlight its suitability for analysing large collections of data in a time-efficient manner
On the Complex Network Structure of Musical Pieces: Analysis of Some Use Cases from Different Music Genres
This paper focuses on the modeling of musical melodies as networks. Notes of
a melody can be treated as nodes of a network. Connections are created whenever
notes are played in sequence. We analyze some main tracks coming from different
music genres, with melodies played using different musical instruments. We find
out that the considered networks are, in general, scale free networks and
exhibit the small world property. We measure the main metrics and assess
whether these networks can be considered as formed by sub-communities. Outcomes
confirm that peculiar features of the tracks can be extracted from this
analysis methodology. This approach can have an impact in several multimedia
applications such as music didactics, multimedia entertainment, and digital
music generation.Comment: accepted to Multimedia Tools and Applications, Springe
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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
Realization of Semantic Atom Blog
Web blog is used as a collaborative platform to publish and share
information. The information accumulated in the blog intrinsically contains the
knowledge. The knowledge shared by the community of people has intangible value
proposition. The blog is viewed as a multimedia information resource available
on the Internet. In a blog, information in the form of text, image, audio and
video builds up exponentially. The multimedia information contained in an Atom
blog does not have the capability, which is required by the software processes
so that Atom blog content can be accessed, processed and reused over the
Internet. This shortcoming is addressed by exploring OWL knowledge modeling,
semantic annotation and semantic categorization techniques in an Atom blog
sphere. By adopting these techniques, futuristic Atom blogs can be created and
deployed over the Internet
Quantum theory-inspired search
With the huge number and diversity of the users, the advertising products and services, the rapid growth of online multimedia resources, the context of information needs are even more broad and complex. Although research in search engine technology has led to various models over the past three decades, the investigation for effectively integrating the dimensions of context to deploy advanced search technology has been limited due to the lack of a unified modeling and evaluation framework. Quantum Theory (QT) has created new and unprecedented means for communicating and computing. Besides computer science, optics, electronics, physics, QT and search engine technology can be combined: interference in user interaction; entanglement in cognition; superposition in word meaning; non-classical probability in information ranking; complex vector spaces in multimedia search. This paper highlights our recent results on QT-inspired search engine technology
Big Data Model Simulation on a Graph Database for Surveillance in Wireless Multimedia Sensor Networks
Sensors are present in various forms all around the world such as mobile
phones, surveillance cameras, smart televisions, intelligent refrigerators and
blood pressure monitors. Usually, most of the sensors are a part of some other
system with similar sensors that compose a network. One of such networks is
composed of millions of sensors connect to the Internet which is called
Internet of things (IoT). With the advances in wireless communication
technologies, multimedia sensors and their networks are expected to be major
components in IoT. Many studies have already been done on wireless multimedia
sensor networks in diverse domains like fire detection, city surveillance,
early warning systems, etc. All those applications position sensor nodes and
collect their data for a long time period with real-time data flow, which is
considered as big data. Big data may be structured or unstructured and needs to
be stored for further processing and analyzing. Analyzing multimedia big data
is a challenging task requiring a high-level modeling to efficiently extract
valuable information/knowledge from data. In this study, we propose a big
database model based on graph database model for handling data generated by
wireless multimedia sensor networks. We introduce a simulator to generate
synthetic data and store and query big data using graph model as a big
database. For this purpose, we evaluate the well-known graph-based NoSQL
databases, Neo4j and OrientDB, and a relational database, MySQL.We have run a
number of query experiments on our implemented simulator to show that which
database system(s) for surveillance in wireless multimedia sensor networks is
efficient and scalable
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