BTU DBIS' Personal Photo Retrieval Runs at ImageCLEF 2013.
Thomas Böttcher, David Zellhöfer, Ingo Schmitt · CLEF (Working Notes) · 2013
This paper summarizes the results of the BTU DBIS research group’s participation in the Personal Photo Retrieval subtask of ImageCLEF 2013. In order to solve the subtask, a self-developed multimodal multimedia retrieval system, PythiaSearch, is used. The discussed retrieval approaches focus on two different strategies. First, two automatic approaches that combine visual features and meta data are examined. Second, a manually assisted relevance feedback approach is presented. All approaches are based on a special query language, CQQL, which supports the logical combination of different features. Considering only automatic runs without relevance feedback that have been submitted to the subtask, DBIS reached the best overall results, while the relevance feedback-assisted approach is placed second amongst all participants of the subtask.