Ontology-Based Inter-concept Relation Fusion for Concept Detection

Although detectors for individual concepts have been widely studied in multimedia search area, the exploration of inter-concept relations among concepts receives relatively less attention, especially when hierarchical concept taxonomy is not manually constructed beforehand. In this paper, we present an ontology-based concept fusion method for building more reliable concept detectors from multiple independent detectors. Specifically, two logical relations among concepts are defined in advance so that an ontology hierarchy can be explicitly built by using a decision rule based on a relation strength function. With the ontology hierarchy built, an effective fusion strategy is then explored to construct an improved detector for each concept. Evaluation on TRECVID'06 test set shows that the proposed method achieves more remarkable and consistent improvement.