How to Find Interesting Locations in Video: A Spatiotemporal Interest Point Detector Learned from Human Eye movements

Interest point detection in still images is a well-studied topic in computer vision. In the spatiotemporal domain, however, it is still unclear which features indicate useful interest points. In this paper we approach the problem by emph{learning} a detector from examples: we record eye movements of human subjects watching video sequences and train a neural network to predict which locations are likely to become eye movement targets. We show that our detector outperforms current spatiotemporal interest point architectures on a standard classification dataset.

In  Pattern Recognition

Publisher  Springer

Details

TypeInproceedings
URL10.1007/978-3-540-74936-3_41
Pages405-414
OrganizationMax-Planck-Gesellschaft
AddressBerlin, Germany
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