Reusing Annotation Labor for Concept Selection


Aly, Robin and Hiemstra, Djoerd and Vries, Arjen de (2009) Reusing Annotation Labor for Concept Selection. In: 8th ACM International Conference on Image and Video Retrieval, 8-10 Jul 2009, Santorini, Greece (pp. p. 44).

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Abstract:Describing shots through the occurrence of semantic concepts is the first step towards modeling the content of a video semantically. An important challenge is to automatically select the right concepts for a given information need. For example, systems should be able to decide whether the concept ``Outdoor'' should be included into a search for ``Street Basketball''. In this paper we provide an innovative method to automatically select concepts for an information need. To achieve this, we provide an estimation for the occurrence probability of a concept in relevant shots, which helps us to quantify the helpfulness of a concept. Our method re-uses existing training data which is annotated with concept occurrences to build a text collection. Searching in this collection with a text retrieval system and knowing about the concept occurrences allows us to come up with a good estimate for this probability. We evaluate our method against a concept selection benchmark and search runs on both the TRECVID 2005 and 2007 collections. These experiments show that the estimation consistently improves retrieval effectiveness.
Item Type:Conference or Workshop Item
Copyright:© 2009 ACM
Electrical Engineering, Mathematics and Computer Science (EEMCS)
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