Collaborative Feature Maps for Interactive Video Search

Publication date

2017

Authors

Schoeffmann, K.
Primus, Manfred J.
Münzer, B.
Petscharnig, Stefan
Karisch, Christof
Xu, Qing
Hürst, WolfgangISNI 000000035205226X

Editors

Advisors

Supervisors

Document Type

Part of book
Open Access logo

License

taverne

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.

Keywords

Taverne

Citation

Schoeffmann, K, Primus, M J, Münzer, B, Petscharnig, S, Karisch, C, Xu, Q & Hürst, W O 2017, Collaborative Feature Maps for Interactive Video Search. in MultiMedia modeling : 23rd International Conference, MMM 2017, Reykjavik, Iceland, January 4-6, 2017, Proceedings. Lecture Notes in Computer Science , vol. 10133, Springer, pp. 457-462. https://doi.org/10.1007/978-3-319-51814-5_41