Linking visual cues and semantic terms under specific digital video domains

Semantic retrieval from video databases is becoming a very important resear ch topic in the area of multimedia. This kind of tasks require the developm ent of video data representation models which include the relationships bet ween low-level visual cues and the semantic concepts inferred from them. Th is paper presents a work based on semiotic studies that includes the extrac tion of simple visual features from commercials and a statistical analysis of them and their relationships with high-level semantic terms. Well-known algorithms have been implemented and enhanced for feature extraction, as we ll as a novel probabilistic approach to color naming. The statistical analy sis consists of finding correlations between variables, as well as the dime nsions in feature space that best explain the variance of the data set. Som e interesting conclusions are reached at the end of the work about how comm ercials are grouped in feature space with respect to different levels of se mantics. (C) 2000 Academic Press.