We present a new approach for collaborative video search and video browsing relying on a combination of traditional, indexbased video retrieval complemented with large-scale human-based visual inspection. In particular, a traditional PC interface is used for query-based search using advanced indexing and querying methods (e.g., concept search), whereas a visualization of the database on a tablet is used for pure human-based browsing. Both parts are coupled to compensate for mutual disadvantages; human visual inspection allows for a better, more detailed analysis of the data -also bridging the semantic gap -but comes at the price of an unfiltered database -a disadvantage that is resolved by using the results from the query engine to change visualization order.

We present an interface for interactive video browsing where users visually skim storyboard representations of the files in search for known items (known-item search tasks) and textually described subjects, objects, or events (ad-hoc search tasks). Individual segments of the video are represented as a color-sorted storyboard that can be addressed via a color-index. Our storyboard representation is optimized for quick visual inspections considering results from our ongoing research. In addition, a concept based-search is used to filter out parts of the storyboard containing the related concept(s), thus complementing the human-based visual inspection with a semantic, content-based annotation.