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M. Zaharieva:
"An Adaptive Clustering Approach for the Diversification of Image Retrieval Results";
Vortrag: MediaEval 2016, Hilversum, The Netherlands; 20.10.2016 - 21.10.2016; in: "CEUR Workshop Proceedings of the MediaEval 2016 Multimedia Benchmark Workshop", ceur-ws.org, Vol-1739 (2016), ISSN: 1613-0073; 3 S.

In this paper, we explore the application of an adaptive clustering approach for the diversification of image retrieval results in the context of the MediaEval 2016 Retrieving Diverse Social Images Task. The proposed approach exploits available textual descriptions, the visual content of the images, and a set of common clustering techniques to select the best combination for each image query individually and in an unsupervised manner.

In this paper, we explore the application of an adaptive clustering approach for the diversification of image retrieval results in the context of the MediaEval 2016 Retrieving Diverse Social Images Task. The proposed approach exploits available textual descriptions, the visual content of the images, and a set of common clustering techniques to select the best combination for each image query individually and in an unsupervised manner.

MediaEval, diversification

http://publik.tuwien.ac.at/files/publik_252850.pdf

Projektleitung Maia Zaharieva:
Unusual sequences detection in very large video collections