Gaze latent support vector machine for image classification

Abstract

This paper deals with image categorization from weak supervision, e.g. global image labels. We propose to improve the region selection performed in latent variable models such as Latent Support Vector Machine (LSVM) by leveraging human eye movement features collected from an eye-tracker device. We introduce a new model, Gaze Latent Support Vector Machine (G… (More)
DOI: 10.1109/ICIP.2016.7532354

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Cite this paper

@article{Wang2016GazeLS, title={Gaze latent support vector machine for image classification}, author={Xin Wang and Nicolas Thome and Matthieu Cord}, journal={2016 IEEE International Conference on Image Processing (ICIP)}, year={2016}, pages={236-240} }