Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Automatic image annotation and retrieval using weighted feature selection
Multimedia Tools and Applications
Automatic metadata extraction and indexing for reusing e-learning multimedia objects
Workshop on multimedia information retrieval on The many faces of multimedia semantics
Wildfire Wally: a volunteer computing game
Future Play '07 Proceedings of the 2007 conference on Future Play
Games with a Purpose for the Semantic Web
IEEE Intelligent Systems
Designing games with a purpose
Communications of the ACM - Designing games with a purpose
KissKissBan: a competitive human computation game for image annotation
Proceedings of the ACM SIGKDD Workshop on Human Computation
A demonstration of human computation using the Phrase Detectives annotation game
Proceedings of the ACM SIGKDD Workshop on Human Computation
Crowdsourcing and the question of expertise
Communications of the ACM - Finding the Fun in Computer Science Education
Designing a language game for collecting coreference annotation
ACL-IJCNLP '09 Proceedings of the Third Linguistic Annotation Workshop
User needs for metadata management in mobile multimedia content services
Mobility '09 Proceedings of the 6th International Conference on Mobile Technology, Application & Systems
An interactive framework for image annotation through gaming
Proceedings of the international conference on Multimedia information retrieval
The next generation authoring adaptive hypermedia: using and evaluating the MOT3.0 and PEAL tools
Proceedings of the 21st ACM conference on Hypertext and hypermedia
The challenge of designing scientific discovery games
Proceedings of the Fifth International Conference on the Foundations of Digital Games
Frontiers of a paradigm: exploring human computation with digital games
Proceedings of the ACM SIGKDD Workshop on Human Computation
Multiple Bernoulli relevance models for image and video annotation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Guess who?: enriching the social graph through a crowdsourcing game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Automatic generation of video narratives from shared UGC
Proceedings of the 22nd ACM conference on Hypertext and hypermedia
Automatic Image Annotation Using Global and Local Features
SMAP '11 Proceedings of the 2011 Sixth International Workshop on Semantic Media Adaptation and Personalization
CBSA: content-based soft annotation for multimodal image retrieval using Bayes point machines
IEEE Transactions on Circuits and Systems for Video Technology
Personal image tagging: a game-based approach
Proceedings of the 8th International Conference on Semantic Systems
Semantics Discovery via Human Computation Games
International Journal on Semantic Web & Information Systems
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Effective acquisition of descriptive semantics for images is still an open issue today. Crowd-based human computation represents a family of approaches able to provide large scale metadata with decent quality. Within this field, games with a purpose (GWAP) have become increasingly important, as they have the potential to motivate contributors to the process through entertainment. However, the existing solutions are weak, when specific metadata are needed. In this work, we present a game with a purpose called PexAce, which utilizes manpower to collect tags characterizing a set of given images. Using novel game mechanics, the game is a single-player, less prone to cold-start problems and suitable for deployment in the domain of personal imagery. As our experiments show, the game delivers tags that characterize images with high precision (using a posteriori expert evaluation and evaluation against the gold standard: the extended Corel 5k dataset). We also employ the game in the domain of personal images, where very specific metadata are needed for their proper organization (person names, places, events) and show, that the game is able to collect even these kinds of metadata. We show that the key to higher quality metadata lies in combining the fun factor of the game with motivation for personal gain.