7,580 research outputs found
Retrieval and Registration of Long-Range Overlapping Frames for Scalable Mosaicking of In Vivo Fetoscopy
Purpose: The standard clinical treatment of Twin-to-Twin Transfusion Syndrome
consists in the photo-coagulation of undesired anastomoses located on the
placenta which are responsible to a blood transfer between the two twins. While
being the standard of care procedure, fetoscopy suffers from a limited
field-of-view of the placenta resulting in missed anastomoses. To facilitate
the task of the clinician, building a global map of the placenta providing a
larger overview of the vascular network is highly desired. Methods: To overcome
the challenging visual conditions inherent to in vivo sequences (low contrast,
obstructions or presence of artifacts, among others), we propose the following
contributions: (i) robust pairwise registration is achieved by aligning the
orientation of the image gradients, and (ii) difficulties regarding long-range
consistency (e.g. due to the presence of outliers) is tackled via a bag-of-word
strategy, which identifies overlapping frames of the sequence to be registered
regardless of their respective location in time. Results: In addition to visual
difficulties, in vivo sequences are characterised by the intrinsic absence of
gold standard. We present mosaics motivating qualitatively our methodological
choices and demonstrating their promising aspect. We also demonstrate
semi-quantitatively, via visual inspection of registration results, the
efficacy of our registration approach in comparison to two standard baselines.
Conclusion: This paper proposes the first approach for the construction of
mosaics of placenta in in vivo fetoscopy sequences. Robustness to visual
challenges during registration and long-range temporal consistency are
proposed, offering first positive results on in vivo data for which standard
mosaicking techniques are not applicable.Comment: Accepted for publication in International Journal of Computer
Assisted Radiology and Surgery (IJCARS
MusA: Using Indoor Positioning and Navigation to Enhance Cultural Experiences in a museum
In recent years there has been a growing interest into the use of multimedia mobile guides in museum environments. Mobile devices have the capabilities to detect the user context and to provide pieces of information suitable to help visitors discovering and following the logical and emotional connections that develop during the visit. In this scenario, location based services (LBS) currently represent an asset, and the choice of the technology to determine users' position, combined with the definition of methods that can effectively convey information, become key issues in the design process. In this work, we present MusA (Museum Assistant), a general framework for the development of multimedia interactive guides for mobile devices. Its main feature is a vision-based indoor positioning system that allows the provision of several LBS, from way-finding to the contextualized communication of cultural contents, aimed at providing a meaningful exploration of exhibits according to visitors' personal interest and curiosity. Starting from the thorough description of the system architecture, the article presents the implementation of two mobile guides, developed to respectively address adults and children, and discusses the evaluation of the user experience and the visitors' appreciation of these application
The DICEMAN description schemes for still images and video sequences
To address the problem of visual content description, two Description Schemes (DSs) developed within the context of a European ACTS project known as DICEMAN, are presented. The DSs, designed based on an analogy with well-known tools for document description, describe both the structure and semantics of still images and video
sequences. The overall structure of both DSs including the various sub-DSs and descriptors (Ds) of which they are composed is described. In each case, the hierarchical sub-DS for describing structure can be constructed using
automatic (or semi-automatic) image/video analysis tools. The hierarchical sub-DSs for describing the semantics, however, are constructed by a user. The integration of the two DSs into a video indexing application currently
under development in DICEMAN is also briefly described.Peer ReviewedPostprint (published version
The mosaic test:measuring the effectiveness of colour-based image retrieval
A variety of content-based image retrieval systems exist which enable users to perform image retrieval based on colour content - i.e., colour-based image retrieval. For the production of media for use in television and film, colour-based image retrieval is useful for retrieving specifically coloured animations, graphics or videos from large databases (by comparing user queries to the colour content of extracted key frames). It is also useful to graphic artists creating realistic computer-generated imagery (CGI). Unfortunately, current methods for evaluating colour-based image retrieval systems have 2 major drawbacks. Firstly, the relevance of images retrieved during the task cannot be measured reliably. Secondly, existing methods do not account for the creative design activity known as reflection-in-action. Consequently, the development and application of novel and potentially more effective colour-based image retrieval approaches, better supporting the large number of users creating media for use in television and film productions, is not possible as their efficacy cannot be reliably measured and compared to existing technologies. As a solution to the problem, this paper introduces the Mosaic Test. The Mosaic Test is a user-based evaluation approach in which participants complete an image mosaic of a predetermined target image, using the colour-based image retrieval system that is being evaluated. In this paper, we introduce the Mosaic Test and report on a user evaluation. The findings of the study reveal that the Mosaic Test overcomes the 2 major drawbacks associated with existing evaluation methods and does not require expert participants
A Literature Survey of Cooperative Caching in Content Distribution Networks
Content distribution networks (CDNs) which serve to deliver web objects
(e.g., documents, applications, music and video, etc.) have seen tremendous
growth since its emergence. To minimize the retrieving delay experienced by a
user with a request for a web object, caching strategies are often applied -
contents are replicated at edges of the network which is closer to the user
such that the network distance between the user and the object is reduced. In
this literature survey, evolution of caching is studied. A recent research
paper [15] in the field of large-scale caching for CDN was chosen to be the
anchor paper which serves as a guide to the topic. Research studies after and
relevant to the anchor paper are also analyzed to better evaluate the
statements and results of the anchor paper and more importantly, to obtain an
unbiased view of the large scale collaborate caching systems as a whole.Comment: 5 pages, 5 figure
Second language learning in the context of MOOCs
Massive Open Online Courses are becoming popular educational vehicles through which universities reach out to non-traditional audiences. Many enrolees hail from other countries and cultures, and struggle to cope with the English language in which these courses are invariably offered. Moreover, most such learners have a strong desire and motivation to extend their knowledge of academic English, particularly in the specific area addressed by the course. Online courses provide a compelling opportunity for domain-specific language learning. They supply a large corpus of interesting linguistic material relevant to a particular area, including supplementary images (slides), audio and video. We contend that this corpus can be automatically analysed, enriched, and transformed into a resource that learners can browse and query in order to extend their ability to understand the language used, and help them express themselves more fluently and eloquently in that domain. To illustrate this idea, an existing online corpus-based language learning tool (FLAX) is applied to a Coursera MOOC entitled Virology 1: How Viruses Work, offered by Columbia University
Exploring the effectiveness of similarity-based visualisations for colour-based image retrieval
In April 2009, Google Images added a filter for narrowing search results by colour. Several other systems for searching image databases by colour were also released around this time. These colour-based image retrieval systems enable users to search image databases either by selecting colours from a graphical palette (i.e., query-by-colour), by drawing a representation of the colour layout sought (i.e., query-by-sketch), or both. It was comments left by readers of online articles describing these colour-based image retrieval systems that provided us with the inspiration for this research. We were surprised to learn that the underlying query-based technology used in colour-based image retrieval systems today remains remarkably similar to that of systems developed nearly two decades ago. Discovering this ageing retrieval approach, as well as uncovering a large user demographic requiring image search by colour, made us eager to research more effective approaches for colour-based image retrieval. In this thesis, we detail two user studies designed to compare the effectiveness of systems adopting similarity-based visualisations, query-based approaches, or a combination of both, for colour-based image retrieval. In contrast to query-based approaches, similarity-based visualisations display and arrange database images so that images with similar content are located closer together on screen than images with dissimilar content. This removes the need for queries, as users can instead visually explore the database using interactive navigation tools to retrieve images from the database. As we found existing evaluation approaches to be unreliable, we describe how we assessed and compared systems adopting similarity-based visualisations, query-based approaches, or both, meaningfully and systematically using our Mosaic Test - a user-based evaluation approach in which evaluation study participants complete an image mosaic of a predetermined target image using the colour-based image retrieval system under evaluation
The crowd as a cameraman : on-stage display of crowdsourced mobile video at large-scale events
Recording videos with smartphones at large-scale events such as concerts and festivals is very common nowadays. These videos register the atmosphere of the event as it is experienced by the crowd and offer a perspective that is hard to capture by the professional cameras installed throughout the venue. In this article, we present a framework to collect videos from smartphones in the public and blend these into a mosaic that can be readily mixed with professional camera footage and shown on displays during the event. The video upload is prioritized by matching requests of the event director with video metadata, while taking into account the available wireless network capacity. The proposed framework's main novelty is its scalability, supporting the real-time transmission, processing and display of videos recorded by hundreds of simultaneous users in ultra-dense Wi-Fi environments, as well as its proven integration in commercial production environments. The framework has been extensively validated in a controlled lab setting with up to 1 000 clients as well as in a field trial where 1 183 videos were collected from 135 participants recruited from an audience of 8 050 people. 90 % of those videos were uploaded within 6.8 minutes
The Exploitation of Data from Remote and Human Sensors for Environment Monitoring in the SMAT Project
In this paper, we outline the functionalities of a system that integrates and
controls a fleet of Unmanned Aircraft Vehicles (UAVs). UAVs have a set of payload sensors
employed for territorial surveillance, whose outputs are stored in the system and analysed
by the data exploitation functions at different levels. In particular, we detail the second
level data exploitation function whose aim is to improve the sensors data interpretation in
the post-mission activities. It is concerned with the mosaicking of the aerial images and
the cartography enrichment by human sensors—the social media users. We also describe
the software architecture for the development of a mash-up (the integration of information
and functionalities coming from the Web) and the possibility of using human sensors in the
monitoring of the territory, a field in which, traditionally, the involved sensors were only the
hardware ones.JRC.H.6-Digital Earth and Reference Dat
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