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 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.

• Type: Conference
• Year: 2007
• Where: DAGM
• Authors: Wolf Kienzle, Bernhard Schölkopf, Felix A. Wichmann, Matthias O. Franz
• Keywords: DAGM 2007, Eye Movement, Image Processing, Interest Point Detection, Spatiotemporal Domain