Compositional Models for Video Event Detection: A Multiple Kernel Learning Latent Variable Approach

Abstract

We present a compositional model for video event detection. A video is modeled using a collection of both global and segment-level features and kernel functions are employed for similarity comparisons. The locations of salient, discriminative video segments are treated as a latent variable, allowing the model to explicitly ignore portions of the video that… (More)
DOI: 10.1109/ICCV.2013.463

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@article{Vahdat2013CompositionalMF, title={Compositional Models for Video Event Detection: A Multiple Kernel Learning Latent Variable Approach}, author={Arash Vahdat and Kevin J. Cannons and Greg Mori and Sangmin Oh and Ilseo Kim}, journal={2013 IEEE International Conference on Computer Vision}, year={2013}, pages={1185-1192} }