Collaborative Feature Maps for Interactive Video Search (bibtex)
@InProceedings{Schoeffmann2017MMM, title = {Collaborative Feature Maps for Interactive Video Search}, author = {Schoeffmann, Klaus and Primus, Manfred Jürgen and Muenzer, Bernd and Petscharnig, Stefan and Karisch, Christoph and Xu, Qing and Huerst, Wolfgang}, booktitle = {MultiMedia Modeling: 23rd International Conference, MMM 2017, Reykjavik, Iceland, January 4-6, 2017, Proceedings, Part II}, year = {2017}, address = {Cham}, editor = {Amsaleg, Laurent and Guðmundsson, Gylfi Þór and Gurrin, Cathal and Jónsson, Björn Þór and Satoh, Shin’ichi}, month = {jan}, pages = {457-462}, publisher = {Springer International Publishing}, abstract = {This extended demo paper summarizes our interface used for the Video Browser Showdown (VBS) 2017 competition, where visual and textual known-item search (KIS) tasks, as well as ad-hoc video search (AVS) tasks in a 600-h video archive need to be solved interactively. To this end, we propose a very flexible distributed video search system that combines many ideas of related work in a novel and collaborative way, such that several users can work together and explore the video archive in a complementary manner. The main interface is a perspective Feature Map, which shows keyframes of shots arranged according to a selected content similarity feature (e.g., color, motion, semantic concepts, etc.). This Feature Map is accompanied by additional views, which allow users to search and filter according to a particular content feature. For collaboration of several users we provide a cooperative heatmap that shows a synchronized view of inspection actions of all users. Moreover, we use collaborative re-ranking of shots (in specific views) based on retrieved results of other users.}, doi = {10.1007/978-3-319-51814-5_41}, language = {EN}, location = {Reykjavik, Iceland}, talkdate = {2017.01.04}, talktype = {registered}, url = {} }
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