Benchmarking result diversification in social image retrieval

Image Processing(2014)

引用 10|浏览54
暂无评分
摘要
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.
更多
查看译文
关键词
image retrieval,social networking (online),MediaEval 2013 benchmarking,crowdsourcing annotations,expert annotations,retrieval result diversification,social image retrieval,crowdsourcing,image content description,re-ranking,result diversification,social photo retrieval
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要