DocumentCode
2281630
Title
KnownStyleNoLife.com: Resource Sharing System for Explicit Fashion-Related Image Annotation
Author
Toyama, Toshiaki ; Konishi, Katsumi
Author_Institution
Depertment of Comput. Sci. & Commun. Eng., Kogakuin Univ., Tokyo
Volume
3
fYear
2008
fDate
9-12 Dec. 2008
Firstpage
152
Lastpage
156
Abstract
In this paper, we present the Web-based resource sharing system KnownStyleNoLife, which allows users explicitly annotate fashion-related images. KnownStyleNoLife harnesses human power and collects image metadata such as object locations, object labels, image rating and semantic relationships among images. Metadata of that type are invaluable as it is difficult for ordinary computer software to extract equivalent metadata from the Web. Acquiring image metadata such as the type and location of objects in images requires a computer to use machine learning techniques, needing training with sample images and Web search techniques, with the outcome that only limited image metadata are extracted. Furthermore, the semantic image relationship metadata is based upon peoplepsilas image perception, hence user feedback is required to acquire it. KnownStyleNoLife provides a social value to users in return for their explicit annotations. It is a novel approach to harness human power to acquire relevant image metadata.
Keywords
image retrieval; image sampling; learning (artificial intelligence); meta data; resource allocation; semantic Web; social networking (online); KnownStyleNoLife; Web search; explicit fashion-related image annotation; image perception; image sample training; machine learning technique; resource sharing system; semantic image relationship metadata; user feedback; Collaborative tools; Computer science; Computer vision; Humans; Informatics; Intelligent agent; Power engineering and energy; Resource management; Software; Tagging; Distributed knowledge acquisition; Image annotation; Semantic annotation; Social Web; fashion community;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on
Conference_Location
Sydney, NSW
Print_ISBN
978-0-7695-3496-1
Type
conf
DOI
10.1109/WIIAT.2008.187
Filename
4740749
Link To Document