LNSMM: Eye Gaze Estimation With Local Network Share Multiview Multitask

• URL: http://arxiv.org/abs/2101.07116v1
• Date: Mon, 18 Jan 2021 15:14:24 GMT
• Title: LNSMM: Eye Gaze Estimation With Local Network Share Multiview Multitask
• Authors: Yong Huang, Ben Chen, Daiming Qu
• Abstract summary: We propose a novel methodology to estimate eye gaze points and eye gaze directions simultaneously. The experiment show our method is state-of-the-art the current mainstream methods on two indicators of gaze points and gaze directions.
• Score: 7.065909514483728
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Eye gaze estimation has become increasingly significant in computer vision.In this paper,we systematically study the mainstream of eye gaze estimation methods,propose a novel methodology to estimate eye gaze points and eye gaze directions simultaneously.First,we construct a local sharing network for feature extraction of gaze points and gaze directions estimation,which can reduce network computational parameters and converge quickly;Second,we propose a Multiview Multitask Learning (MTL) framework,for gaze directions,a coplanar constraint is proposed for the left and right eyes,for gaze points,three views data input indirectly introduces eye position information,a cross-view pooling module is designed, propose joint loss which handle both gaze points and gaze directions estimation.Eventually,we collect a dataset to use of gaze points,which have three views to exist public dataset.The experiment show our method is state-of-the-art the current mainstream methods on two indicators of gaze points and gaze directions.

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