DocumentCode
248828
Title
Benchmarking result diversification in social image retrieval
Author
Ionescu, Bogdan ; Popescu, Adrian ; Muller, Holger ; Menendez, Maria ; Radu, Anca-Livia
Author_Institution
Univ. Politeh. of Bucharest, Bucharest, Romania
fYear
2014
fDate
27-30 Oct. 2014
Firstpage
3072
Lastpage
3076
Abstract
This article addresses the issue of retrieval result diversification in the context of social image retrieval and discusses the results achieved during the MediaEval 2013 benchmarking. 38 runs and their results are described and analyzed in this text. A comparison of the use of expert vs. crowdsourcing annotations shows that crowdsourcing results are slightly different and have higher inter observer differences but results are comparable at lower cost. Multimodal approaches have best results in terms of cluster recall. Manual approaches can lead to high precision but often lower diversity. With this detailed results analysis we give future insights on this matter.
Keywords
image retrieval; social networking (online); MediaEval 2013 benchmarking; crowdsourcing annotations; expert annotations; retrieval result diversification; social image retrieval; Benchmark testing; Cultural differences; Global Positioning System; Image retrieval; Media; Optimization; Visualization; crowdsourcing; image content description; re-ranking; result diversification; social photo retrieval;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location
Paris
Type
conf
DOI
10.1109/ICIP.2014.7025621
Filename
7025621
Link To Document