DocumentCode :
2917283
Title :
Image annotation through gaming (TAG4FUN)
Author :
Seneviratne, L. ; Izquierdo, E.
Author_Institution :
Multimedia & Vision Res. Group, Queen Mary, Univ. of London, London, UK
fYear :
2009
fDate :
5-7 July 2009
Firstpage :
1
Lastpage :
6
Abstract :
This paper introduces a new technique for image annotation in which social aspects of human-based computation are exploited. The proposed approach aims at exploiting what millions of single, online and cooperative gamers are keen to do, (in some cases gaming enthusiasts) to tackle the challenging image annotation task. The proposed approach deviates from the conventional "content-based image retrieval (CBIR)" paradigm, favored by the research community to tackle problems related to semantic annotation and tagging of multimedia content. The proposed approach focuses on social aspects of gaming and the use of humans in a widely distributed fashion through a process of human-based computation. It aims at motivating people towards image tagging while entertaining themselves. Regarding key aspect of label accuracy, a combination of computer vision techniques, machine learning and game strategies have been used.
Keywords :
computer games; computer vision; content-based retrieval; human factors; image retrieval; interactive systems; learning (artificial intelligence); TAG4FUN game; computer vision technique; content-based image retrieval; cooperative gamer; human-based computation; image annotation; image tagging; interactive game; machine learning; multimedia content; semantic annotation; Computer vision; Content based retrieval; Games; Humans; Image retrieval; Labeling; Machine learning; Object recognition; Psychology; Tagging; Image Annotation; Interactive gaming; Lowlevel feature extraction and object recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Signal Processing, 2009 16th International Conference on
Conference_Location :
Santorini-Hellas
Print_ISBN :
978-1-4244-3297-4
Electronic_ISBN :
978-1-4244-3298-1
Type :
conf
DOI :
10.1109/ICDSP.2009.5201118
Filename :
5201118
Link To Document :
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