Automatic fine-grained hyperlinking of videos within a closed collection using scene segmentation

This paper introduces a framework for establishing links between related media fragments within a collection of videos. A set of analysis techniques is applied for extracting information from dierent types of data. Visual-based shot and scene segmentation is performed for dening media fragments at dierent granularity levels, while visual cues are detected from keyframes of the video via concept detection

and optical character recognition (OCR). Keyword extraction is applied on textual data such as the output of OCR, subtitles and metadata. This set of results is used for the

automatic identication and linking of related media fragments. The proposed framework exhibited competitive performance in the Video Hyperlinking sub-task of MediaEval

2013, indicating that video scene segmentation can provide more meaningful segments, compared to other decomposition methods, for hyperlinking purposes.