摘要

We propose the Hierarchical Detection Network (HDN) for the detection of facial palsy syndrome. This can be the first deep-learning based approach for the facial palsy detection. The proposed HDN consists of three component networks, the first detects faces, the second detects the landmarks on the detected faces, and the third detects the local palsy regions. The first and the third component networks are built on the Darknet framework, but with fewer layers of convolutions for shorter processing speed. The second component network employs the latest 3D face alignment network for locating the landmarks. The first component network employs a Na × Na grid over the overall input image, while the third component network employs a Nb × Nb grid over each detected face, making the HDN capable of efficiently locating the affected palsy regions. As previous approaches were evaluated on proprietary databases, we have collected 32 videos from YouTube and made the first public database for facial palsy study. To enhance the robustness against expression variations, we include the CK+ facial expression database in the training and testing phases. We show that the HDN does not just detect the local palsy regions, but also captures the frequency of the intensity, enabling the video-to-description diagnosis of the syndrome. Experiments show that the proposed approach offers an accurate and efficient solution for facial palsy detection/diagnosis.

原文英語
主出版物標題Proceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2018
發行者IEEE Computer Society
頁面693-699
頁數7
ISBN(電子)9781538661000
DOIs
出版狀態已發佈 - 12月 13 2018
事件31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2018 - Salt Lake City, 美国
持續時間: 6月 18 20186月 22 2018

出版系列

名字IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
2018-June
ISSN(列印)2160-7508
ISSN(電子)2160-7516

會議

會議31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2018
國家/地區美国
城市Salt Lake City
期間6/18/186/22/18

ASJC Scopus subject areas

  • 電腦視覺和模式識別
  • 電氣與電子工程

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