Abstract
This paper describes a video browsing tool for media (post-) production, enabling users to efficiently find relevant media items for redundant and sparsely annotated content collections. Users can iteratively cluster the content set by different features, and restrict the content set by selecting a subset of clusters. In addition to clustering by features, similarity search by different features is supported, and a set of linked video segments can be explored for a segment of interest. Desktop and Web-based variants of the user interface, including temporal preview functionality, are available. © 2014 Springer International Publishing.
Cite
CITATION STYLE
Bailer, W., Weiss, W., Schober, C., & Thallinger, G. (2014). Browsing linked video collections for media production. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8326 LNCS, pp. 407–410). https://doi.org/10.1007/978-3-319-04117-9_47
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