117,385 research outputs found
Adaptive Tag Selection for Image Annotation
Not all tags are relevant to an image, and the number of relevant tags is
image-dependent. Although many methods have been proposed for image
auto-annotation, the question of how to determine the number of tags to be
selected per image remains open. The main challenge is that for a large tag
vocabulary, there is often a lack of ground truth data for acquiring optimal
cutoff thresholds per tag. In contrast to previous works that pre-specify the
number of tags to be selected, we propose in this paper adaptive tag selection.
The key insight is to divide the vocabulary into two disjoint subsets, namely a
seen set consisting of tags having ground truth available for optimizing their
thresholds and a novel set consisting of tags without any ground truth. Such a
division allows us to estimate how many tags shall be selected from the novel
set according to the tags that have been selected from the seen set. The
effectiveness of the proposed method is justified by our participation in the
ImageCLEF 2014 image annotation task. On a set of 2,065 test images with ground
truth available for 207 tags, the benchmark evaluation shows that compared to
the popular top- strategy which obtains an F-score of 0.122, adaptive tag
selection achieves a higher F-score of 0.223. Moreover, by treating the
underlying image annotation system as a black box, the new method can be used
as an easy plug-in to boost the performance of existing systems
Creation of virtual worlds from 3D models retrieved from content aware networks based on sketch and image queries
The recent emergence of user generated content requires new content creation tools that will be both easy to learn and easy to use. These new tools should enable the user to construct new high-quality content with minimum effort; it is essential to allow existing multimedia content to be reused as building blocks when creating new content. In this work we present a new tool for automatically constructing virtual worlds with minimum user intervention. Users can create these worlds by drawing a simple sketch, or by using interactively segmented 2D objects from larger images. The system receives as a query the sketch or the segmented image, and uses it to find similar 3D models that are stored in a Content Centric Network. The user selects a suitable model from the retrieved models, and the system uses it to automatically construct a virtual 3D world
Digital Image Access & Retrieval
The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio
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