Collaborative Video Retrieval

We are currently working on collaborative video search systems, where several users work together to jointly retrieve information in a large video archive. As shown in the figure below, this allows for fast and flexible content-based search where

  • several users perform the same type of search but in different areas of the video collection, or
  • several users perform different types of search (e.g., one searches by semantic concept browsing, the second one by color sketches/queries, and the third one by motion sketches/queries), but work together to speed-up the whole search process. This way different users follow different search paths and perform distributed facet-based search.


Collaborative Video Search


In either way, the search system of each user needs to communicate with the systems of the other users in order to perform some kind of synchronization. In our system (used for VBS 2017) this is provided through the following features:

  • a collaborative mini map that communicates with all connected systems and shows what content is currently inspected by all users (and has been inspected).
  • automatic collaborative re-ranking of retrieved results, such that already inspected videos are down-ranked, while unchecked content is up-ranked.
  • manual notifications among users to make search colleagues aware of interesting areas in the video collection.


The figure below shows how a sophisticated video retrieval tool could work together with a mobile video browsing tool (optimized for visual human inspection), in a way that both systems benefit from each other.


If you want to know more details about collaborative video search, here are a few papers:


ViDive Screenshot 1ViDive Screenshot 2