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Erschienen in:
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2020 | OriginalPaper | Buchkapitel

Emotion Recognition with Facial Landmark Heatmaps

verfasst von : Siyi Mo, Wenming Yang, Guijin Wang, Qingmin Liao

Erschienen in: MultiMedia Modeling

Verlag: Springer International Publishing

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Abstract

Facial expression recognition is a very challenging problem and has attracted more and more researchers’ attention. In this paper, considering that facial expression recognition is closely related to the features of key facial regions, we propose a facial expression recognition network that explicitly utilizes the landmark heatmap information to precisely capture the most discriminative features. In addition to directly adding the information of facial fiducial points in the form of landmark heatmaps, we also propose an end-to-end network structure--heatmap aiding emotion network (HAE-Net) by embedding the landmark detection module based on stack-based hourglass network into the facial expression recognition network. Experiments on CK+, RAF and AffectNet databases show that our method achieves better results compared with the state-of-the-art methods, which demonstrates that adding additional landmark information, as well as joint training of landmark detection and expression recognition, are beneficial to improve recognition performance.

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Vorheriges Kapitel Eulerian Motion Based 3DCNN Architecture for Facial Micro-Expression Recognition
Nächstes Kapitel One-Shot Face Recognition with Feature Rectification via Adversarial Learning
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Metadaten
Titel
Emotion Recognition with Facial Landmark Heatmaps
verfasst von
Siyi Mo
Wenming Yang
Guijin Wang
Qingmin Liao
Copyright-Jahr
2020
Buch
MultiMedia Modeling

Print ISBN: 978-3-030-37730-4

Electronic ISBN: 978-3-030-37731-1

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-37731-1_23

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