Building Detectors to Support Searches on Combined Semantic Concepts

by Robin Aly, Djoerd Hiemstra, and Roeland Ordelman

Bridging the semantic gap is one of the big challenges in multimedia information retrieval. It exists between the extraction of low-level features of a video and its conceptual contents. In order to understand the conceptual content of a video a common approach is building concept detectors. A problem of this approach is that the number of detectors is impossible to determine. This paper presents a set of 8 methods on how to combine two existing concepts into a new one, using a logical AND operator. The scores for each shot of a video for the combined concept are computed from the output of the underlying detectors. The findings are evaluated on basis of the output of the 101 detectors including a comparison to the theoretical possibility to train a classifier on each combined concept. The precision gains are significant, specially for methods which also consider the chronological surrounding of a shot promising.

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