ONTOLOGICAL RERANKING APPROACH FOR HYBRID CONCEPT SIMILARITY-BASED VIDEO SHOTS INDEXATION

This paper proposes to compare three hybrid concept similarity measures for video shots indexing and retrieval [1], based on two steps. First, individuals concepts are modeled independently. Second, an ontology is introduced via the representation of the relationship between concepts and the ontological readjustment of the confidence values. Our contribution lies in the manner in which inter-concepts similarities are exploited in the indexing system using co-occurrence, visual descriptors, and hybrid semantic similarities. Experimental results report the efficiency and the significant improvement provided by the proposed scheme.