Movie Description Model for Media Retrieval Services

As the variety of media content increases, consumer services are being asked for more ways to access them. For a better consumer experience, more media attributes should be revealed to connect consumers with media content. Various methods have been studied to extract complicated contexts in media content like entity detection and image/video captioning. Among them, this paper focuses on the movie description. A movie description model manifests comprehensive descriptions of movies concerning story context. Thus, consumer services can provide rich information about movies to users. This paper proposes a novel movie description model with the story background to generate detailed descriptions. The story background entities are included in the movie script during the pre-production stage. These entities have a significant effect on the scene portrayed. We define the story background using the location and time information of the scenes. The models with shot structures extract the story background from a keyframe of each scene to generate the scene description. In experiments with the LSMDC dataset, the proposed model achieves 0.0141 of BLEU@4 and 0.1313 CIDEr, which is about 9% over the baselines. Qualitatively, the description generated through the proposed model provides richer contextual information compared to previous studies.