RDF-powered semantic video annotation tools with concept mapping to Linked Data for next-generation video indexing: a comprehensive review

摘要

Video annotation tools are often compared in the literature, however, most reviews mix unstructured, semi-structured, and the very few structured annotation software. This paper is a comprehensive review of video annotations tools generating structured data output for video clips, regions of interest, frames, and media fragments, with a focus on Linked Data support. The tools are compared in terms of supported input and output data formats, expressivity, annotation specificity, spatial and temporal fragmentation, the concept mapping sources used for Linked Open Data (LOD) interlinking, provenance data support, and standards alignment. Practicality and usability aspects of the user interface of these tools are highlighted. Moreover, this review distinguishes extensively researched yet discontinued semantic video annotation software from promising state-of-the-art tools that show new directions in this increasingly important field.