15,059 research outputs found
Video browsing interfaces and applications: a review
We present a comprehensive review of the state of the art in video browsing and retrieval systems, with special emphasis on interfaces and applications. There has been a significant increase in activity (e.g., storage, retrieval, and sharing) employing video data in the past decade, both for personal and professional use. The ever-growing amount of video content available for human consumption and the inherent characteristics of video dataâwhich, if presented in its raw format, is rather unwieldy and costlyâhave become driving forces for the development of more effective solutions to present video contents and allow rich user interaction. As a result, there are many contemporary research efforts toward developing better video browsing solutions, which we summarize. We review more than 40 different video browsing and retrieval interfaces and classify them into three groups: applications that use video-player-like interaction, video retrieval applications, and browsing solutions based on video surrogates. For each category, we present a summary of existing work, highlight the technical aspects of each solution, and compare them against each other
STCP: Receiver-agnostic Communication Enabled by Space-Time Cloud Pointers
Department of Electrical and Computer Engineering (Computer Engineering)During the last decade, mobile communication technologies have rapidly evolved and ubiquitous network connectivity is nearly achieved. However, we observe that there are critical situations where none of the existing mobile communication technologies is usable. Such situations are often found when messages need to be delivered to arbitrary persons or devices that are located in a specific space at a specific time. For instance at a disaster scene, current communication methods are incapable of delivering messages of a rescuer to the group of people at a specific area even when their cellular connections are alive because the rescuer cannot specify the receivers of the messages. We name this as receiver-unknown problem and propose a viable solution called SpaceMessaging. SpaceMessaging adopts the idea of Post-it by which we casually deliver our messages to a person who happens to visit a location at a random moment. To enable SpaceMessaging, we realize the concept of posting messages to a space by implementing cloud-pointers at a cloud server to which messages can be posted and from which messages can fetched by arbitrary mobile devices that are located at that space. Our Android-based prototype of SpaceMessaging, which particularly maps a cloud-pointer to a WiFi signal fingerprint captured from mobile devices, demonstrates that it first allows mobile devices to deliver messages to a specific space and to listen to the messages of a specific space in a highly accurate manner (with more than 90% of Recall)
Concept Extraction and Clustering for Topic Digital Library Construction
This paper is to introduce a new approach to build
topic digital library using concept extraction and
document clustering. Firstly, documents in a special
domain are automatically produced by document
classification approach. Then, the keywords of each
document are extracted using the machine learning
approach. The keywords are used to cluster the
documents subset. The clustered result is the taxonomy
of the subset. Lastly, the taxonomy is modified to the
hierarchical structure for user navigation by manual
adjustments. The topic digital library is constructed
after combining the full-text retrieval and hierarchical
navigation function
Info Navigator: A visualization tool for document searching and browsing
In this paper we investigate the retrieval performance of monophonic and polyphonic queries made on a polyphonic music database. We extend the n-gram approach for full-music indexing of monophonic music data to polyphonic music using both rhythm and pitch information. We define an experimental framework for a comparative and fault-tolerance study of various n-gramming strategies and encoding levels. For monophonic queries, we focus in particular on query-by-humming systems, and for polyphonic queries on query-by-example. Error models addressed in several studies are surveyed for the fault-tolerance study. Our experiments show that different n-gramming strategies and encoding precision differ widely in their effectiveness. We present the results of our study on a collection of 6366 polyphonic MIDI-encoded music pieces
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Stacking-based visualization of trajectory attribute data
Visualizing trajectory attribute data is challenging because it involves showing the trajectories in their spatio-temporal context as well as the attribute values associated with the individual points of trajectories. Previous work on trajectory visualization addresses selected aspects of this problem, but not all of them. We present a novel approach to visualizing trajectory attribute data. Our solution covers space, time, and attribute values. Based on an analysis of relevant visualization tasks, we designed the visualization solution around the principle of stacking trajectory bands. The core of our approach is a hybrid 2D/3D display. A 2D map serves as a reference for the spatial context, and the trajectories are visualized as stacked 3D trajectory bands along which attribute values are encoded by color. Time is integrated through appropriate ordering of bands and through a dynamic query mechanism that feeds temporally aggregated information to a circular time display. An additional 2D time graph shows temporal information in full detail by stacking 2D trajectory bands. Our solution is equipped with analytical and interactive mechanisms for selecting and ordering of trajectories, and adjusting the color mapping, as well as coordinated highlighting and dedicated 3D navigation. We demonstrate the usefulness of our novel visualization by three examples related to radiation surveillance, traffic analysis, and maritime navigation. User feedback obtained in a small experiment indicates that our hybrid 2D/3D solution can be operated quite well
A knowledge hub to enhance the learning processes of an industrial cluster
Industrial clusters have been defined as ?networks of production of strongly interdependent firms (including specialised suppliers), knowledge producing agents (universities, research institutes, engineering companies), institutions (brokers, consultants), linked to each other in a value adding production chain? (OECD Focus Group, 1999). The industrial clusters distinctive mode of production is specialisation, based on a sophisticated division of labour, that leads to interlinked activities and need for cooperation, with the consequent emergence of communities of practice (CoPs). CoPs are here conceived as groups of people and/or organisations bound together by shared expertise and propensity towards a joint work (Wenger and Suyden, 1999). Cooperation needs closeness for just-in-time delivery, for communication, for the exchange of knowledge, especially in its tacit form. Indeed the knowledge exchanges between the CoPs specialised actors, in geographical proximity, lead to spillovers and synergies. In the digital economy landscape, the use of collaborative technologies, such as shared repositories, chat rooms and videoconferences can, when appropriately used, have a positive impact on the development of the CoP exchanges process of codified knowledge. On the other end, systems for the individuals profile management, e-learning platforms and intelligent agents can trigger also some socialisation mechanisms of tacit knowledge. In this perspective, we have set-up a model of a Knowledge Hub (KH), driven by the Information and Communication Technologies (ICT-driven), that enables the knowledge exchanges of a CoP. In order to present the model, the paper is organised in the following logical steps: - an overview of the most seminal and consolidated approaches to CoPs; - a description of the KH model, ICT-driven, conceived as a booster of the knowledge exchanges of a CoP, that adds to the economic benefits coming from geographical proximity, the advantages coming from organizational proximity, based on the ICTs; - a discussion of some preliminary results that we are obtaining during the implementation of the model.
CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap
After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in
multimedia search engines, we have identified and analyzed gaps within European research effort during our second year.
In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio-
economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown
of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on
requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the
community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our
Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as
National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core
technological gaps that involve research challenges, and âenablersâ, which are not necessarily technical research
challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal
challenges
Learning to Navigate the Energy Landscape
In this paper, we present a novel and efficient architecture for addressing
computer vision problems that use `Analysis by Synthesis'. Analysis by
synthesis involves the minimization of the reconstruction error which is
typically a non-convex function of the latent target variables.
State-of-the-art methods adopt a hybrid scheme where discriminatively trained
predictors like Random Forests or Convolutional Neural Networks are used to
initialize local search algorithms. While these methods have been shown to
produce promising results, they often get stuck in local optima. Our method
goes beyond the conventional hybrid architecture by not only proposing multiple
accurate initial solutions but by also defining a navigational structure over
the solution space that can be used for extremely efficient gradient-free local
search. We demonstrate the efficacy of our approach on the challenging problem
of RGB Camera Relocalization. To make the RGB camera relocalization problem
particularly challenging, we introduce a new dataset of 3D environments which
are significantly larger than those found in other publicly-available datasets.
Our experiments reveal that the proposed method is able to achieve
state-of-the-art camera relocalization results. We also demonstrate the
generalizability of our approach on Hand Pose Estimation and Image Retrieval
tasks
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