Description

Title Improving Video Search through Serious-game Data
Abstract Serious games are increasingly used in audio-visual collections as a mechanism for annotating videos through tagging. This trend is driven by the assumption that user tags will improve video search. In this paper we study whether this is indeed the case. To this end, we create an evaluation dataset that consists of: (i) a set of videos tagged by users via video labelling game, (ii) a set of queries derived from real-life query logs, and (iii) relevance judgements. Besides user tags from the labelling game, we exploit the existing metadata associated with the videos (textual descriptions and curated in-house tags) and closed captions. Our findings show that search based on user tags alone outperforms search based on all other metadata types. Combining user tags with the other types of metadatayields an increase in search performance of 33%. We also find that search performance of user tags steadily increases as more tags are collected.

Other presentations by Riste Gligorov

DateTitle
05 September 2011 On the Role of User-generated Metadata in Audio Visual Collections
17 December 2012 Improving Video Search through Serious-game Data