@InProceedings{Riegler2013, author = {Riegler, M and Lux, Mathias and Kofler, Ch}, booktitle = {MediaEval 2013 - Multimedia Benchmark Workshop}, title = {Frame the Crowd: Global Visual Features Labeling boosted with Crowdsourcing Information}, year = {2013}, address = {Barcelona, Spain}, editor = {Larson, M and Anguera, X and Reuter, T and Jones, G and Ionescu, B and Schedl, M and Piatrik, T and Hauff, C and Soleymani, M}, month = {October}, pages = {--}, publisher = {CEUR Workshop Proceedings}, abstract = {In this paper we present our approach to the Crowd Sourcing Task of the MediaEval 2013 Benchmark [2] using transfer learning and visual features. For the visual features we adopt an existing approach for search based classification using content based image retrieval on global features with feature selection and feature combination to boost the performance. Our approach gives a baseline evaluation indicating the usefulness of global visual features, hashing and search-based classification.}, edition = {Vol 1043}, language = {EN}, talktype = {none}, url = {http://ceur-ws.org/Vol-1043/} }