Flexible user interface for efficient content-based video surveillance retrieval: design and evaluation

摘要

The major drawback of interactive retrieval systems is the potential frustration of the user that is caused by an excessive labelling work. Active learning has proven to help solving this issue, by carefully selecting the examples to present to the user. In this context, the design of the user interface plays a critical role since it should invite the user to label the examples elected by the active learning. This paper presents the design and evaluation of an innovative user interface for image retrieval. It has been validate using real-life IEEE PETS video surveillance data. In particular, we investigated the most appropriate repartition of the display area between the retrieved video frames and the active learning examples, taking both objective and subjective user satisfaction parameters into account. The flexibility of the interface relies on a scalable representation of the video content such as Motion JPEG 2000 in our implementation.