Two-Stage Learning to Predict Human Eye Fixations via SDAEs

IEEE Transactions on Cybernetics
Junwei HanXuelong Li

Abstract

Saliency detection models aiming to quantitatively predict human eye-attended locations in the visual field have been receiving increasing research interest in recent years. Unlike traditional methods that rely on hand-designed features and contrast inference mechanisms, this paper proposes a novel framework to learn saliency detection models from raw image data using deep networks. The proposed framework mainly consists of two learning stages. At the first learning stage, we develop a stacked denoising autoencoder (SDAE) model to learn robust, representative features from raw image data under an unsupervised manner. The second learning stage aims to jointly learn optimal mechanisms to capture the intrinsic mutual patterns as the feature contrast and to integrate them for final saliency prediction. Given the input of pairs of a center patch and its surrounding patches represented by the features learned at the first stage, a SDAE network is trained under the supervision of eye fixation labels, which achieves both contrast inference and contrast integration simultaneously. Experiments on three publically available eye tracking benchmarks and the comparisons with 16 state-of-the-art approaches demonstrate the effectiveness of the...Continue Reading

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Citations

Sep 1, 2015·IEEE Transactions on Neural Networks and Learning Systems·Jun ZhangXindong Wu
Nov 17, 2015·IEEE Transactions on Neural Networks and Learning Systems·Zhenbao LiuShuhui Bu
Oct 11, 2016·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society· Bo MaFatih Porikli
Oct 16, 2016·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society· Jianbing Shen Ling Shao
Nov 17, 2016·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society· Xiaoqiang Lu Xuelong Li
Mar 2, 2016·IEEE Transactions on Cybernetics· Zhenbao Liu Xuelong Li
Feb 1, 2017·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Dingwen ZhangXiaojun Chang
Mar 19, 2016·IEEE Transactions on Cybernetics·Bo DuDacheng Tao
Feb 22, 2017·IEEE Transactions on Cybernetics·Guanjun GuoXuelong Li
Apr 20, 2017·IEEE Transactions on Neural Networks and Learning Systems·Xuelong LiXiaoqiang Lu
Jul 12, 2017·IEEE Transactions on Cybernetics·Xuelong LiXiaoqiang Lu
Nov 28, 2017·PloS One·Xin XiaHongyan Xu
Oct 14, 2017·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society· Jia Li Xiaowu Chen
Oct 6, 2016·IEEE Transactions on Cybernetics·Shangwen ChenLing Shao
May 29, 2018·Technology in Cancer Research & Treatment·Islam RedaAyman El-Baz
May 27, 2021·Computational Intelligence and Neuroscience·Kengda HuangMeixin Fang

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