17,892 research outputs found
CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines
Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective.
The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines.
From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research
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 “enablers”, 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
Visual Information Retrieval in Endoscopic Video Archives
In endoscopic procedures, surgeons work with live video streams from the
inside of their subjects. A main source for documentation of procedures are
still frames from the video, identified and taken during the surgery. However,
with growing demands and technical means, the streams are saved to storage
servers and the surgeons need to retrieve parts of the videos on demand. In
this submission we present a demo application allowing for video retrieval
based on visual features and late fusion, which allows surgeons to re-find
shots taken during the procedure.Comment: Paper accepted at the IEEE/ACM 13th International Workshop on
Content-Based Multimedia Indexing (CBMI) in Prague (Czech Republic) between
10 and 12 June 201
Hybrid Information Retrieval Model For Web Images
The Bing Bang of the Internet in the early 90's increased dramatically the
number of images being distributed and shared over the web. As a result, image
information retrieval systems were developed to index and retrieve image files
spread over the Internet. Most of these systems are keyword-based which search
for images based on their textual metadata; and thus, they are imprecise as it
is vague to describe an image with a human language. Besides, there exist the
content-based image retrieval systems which search for images based on their
visual information. However, content-based type systems are still immature and
not that effective as they suffer from low retrieval recall/precision rate.
This paper proposes a new hybrid image information retrieval model for indexing
and retrieving web images published in HTML documents. The distinguishing mark
of the proposed model is that it is based on both graphical content and textual
metadata. The graphical content is denoted by color features and color
histogram of the image; while textual metadata are denoted by the terms that
surround the image in the HTML document, more particularly, the terms that
appear in the tags p, h1, and h2, in addition to the terms that appear in the
image's alt attribute, filename, and class-label. Moreover, this paper presents
a new term weighting scheme called VTF-IDF short for Variable Term
Frequency-Inverse Document Frequency which unlike traditional schemes, it
exploits the HTML tag structure and assigns an extra bonus weight for terms
that appear within certain particular HTML tags that are correlated to the
semantics of the image. Experiments conducted to evaluate the proposed IR model
showed a high retrieval precision rate that outpaced other current models.Comment: LACSC - Lebanese Association for Computational Sciences,
http://www.lacsc.org/; International Journal of Computer Science & Emerging
Technologies (IJCSET), Vol. 3, No. 1, February 201
An MPEG-7 scheme for semantic content modelling and filtering of digital video
Abstract Part 5 of the MPEG-7 standard specifies Multimedia Description Schemes (MDS); that is, the format multimedia content models should conform to in order to ensure interoperability across multiple platforms and applications. However, the standard does not specify how the content or the associated model may be filtered. This paper proposes an MPEG-7 scheme which can be deployed for digital video content modelling and filtering. The proposed scheme, COSMOS-7, produces rich and multi-faceted semantic content models and supports a content-based filtering approach that only analyses content relating directly to the preferred content requirements of the user. We present details of the scheme, front-end systems used for content modelling and filtering and experiences with a number of users
Video Data Visualization System: Semantic Classification And Personalization
We present in this paper an intelligent video data visualization tool, based
on semantic classification, for retrieving and exploring a large scale corpus
of videos. Our work is based on semantic classification resulting from semantic
analysis of video. The obtained classes will be projected in the visualization
space. The graph is represented by nodes and edges, the nodes are the keyframes
of video documents and the edges are the relation between documents and the
classes of documents. Finally, we construct the user's profile, based on the
interaction with the system, to render the system more adequate to its
references.Comment: graphic
CHORUS Deliverable 4.5: Report of the 3rd CHORUS Conference
The third and last CHORUS conference on Multimedia Search Engines took place from the 26th to the 27th of May 2009 in Brussels, Belgium. About 100 participants from 15 European countries, the US, Japan and Australia learned about the latest developments in the domain. An exhibition of 13 stands presented 16 research projects currently ongoing around the
world
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