Location: EU Supported » PlanetData » REASE

Semantics for visual resources: Use Cases from E-Culture

author: Guus Schreiber, Vrije Universiteit Amsterdam (VU)
published: Nov. 9, 2011,   recorded: February 2007,   views: 22
released under terms of: Creative Commons Attribution Share Alike (CC-BY-SA)
Categories

See Also:

Download article icon Download article: 150564583988947538121148034913086672033.zip (133.5 MB)

Download article icon Download article: 23722079611659805911361437335640899575.zip (133.5 MB)


Help icon Streaming Video Help

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

This is a one-hour video recording of the presentation of Guus Schreiber at the KnowledgeWeb summer school 2006. It comprises either the video synchronized with the slides (requires Flash) or the video alone.

Table of Contents: Semantics for visual resources Use Cases from E-Culture Purpose Use case: Asian chairs AAT info on Guangxu Importance of time and space information Sample place information in TGN Issues when searching for 'nearby' Asian chairs Use case: painting style How can we find this other Fauve painting? Issues Search: WordNet patterns that increase recall without sacrificing precision (Hollink) Issues w.r.t. thesauri Use case: find images with the same subject Issues Conceptual subject descriptions Example concepts in image Use of conceptual categories by people searching for images Thesauri for scenes: Iconclass Annotation of image content Some forms of image content are well suited to image analysis The semantic gap Example semantic bridge: microscopic cell images Segmentation often requires user interaction Automatic detection of concepts can be difficult even in 'easy' cases Image analysis useful for collection navigation Bridging the semantic gap: CBIR and ontologies Sample visual features and their mapping to WordNet Experiment: pruning the search for 'conveyance' concepts Bridging the semantic gap: concept detectors 'Concepts' for which visual detectors were built LSCOM lexicon: 229 - Weather LSCOM lexicon: 110 - Female Anchor 'Concepts' for which visual detectors were built Natural-lang proc. Main observation

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: