Abstract
An approach to target-based image retrieval is described based on on-line rank-based learning. User feedback obtained via interaction with 2D image layouts provides qualitative constraints that are used to adapt distance metrics for retrieval. The user can change the query during a search session in order to speed up the retrieval process. An empirical comparison of online learning methods including ranking-SVM is reported using both simulated and real users.
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Han, J., McKenna, S.J., Wang, R. (2009). Learning Query-Dependent Distance Metrics for Interactive Image Retrieval. In: Fritz, M., Schiele, B., Piater, J.H. (eds) Computer Vision Systems. ICVS 2009. Lecture Notes in Computer Science, vol 5815. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04667-4_38
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DOI: https://doi.org/10.1007/978-3-642-04667-4_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04666-7
Online ISBN: 978-3-642-04667-4
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