Face Detection and Recognition Based on Visual Attention Mechanism Guidance Model in Unrestricted Posture
Author
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-05-20
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Performance of face detection and recognition is affected and damaged because occlusion often leads to missed detection.
To reduce the recognition accuracy caused by facial occlusion and enhance the accuracy of face detection, a visual attention mechanism guidance model is proposed in this paper, which uses the visual attention mechanism to guide the model highlight the visible area of the occluded face; the face detection problem is simplified into the high-level semantic feature detection problem through the improved analytical network, and the location and scale of the face are predicted by the activation map to avoid additional parameter settings.
A large number of simulation experiment results show that our proposed method is superior to other comparison algorithms for the accuracy of occlusion face detection and recognition on the face database.
In addition, our proposed method achieves a better balance between detection accuracy and speed, which can be used in the field of security surveillance.
American Psychological Association (APA)
Yuan, Zhenguo. 2020. Face Detection and Recognition Based on Visual Attention Mechanism Guidance Model in Unrestricted Posture. Scientific Programming،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1209254
Modern Language Association (MLA)
Yuan, Zhenguo. Face Detection and Recognition Based on Visual Attention Mechanism Guidance Model in Unrestricted Posture. Scientific Programming No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1209254
American Medical Association (AMA)
Yuan, Zhenguo. Face Detection and Recognition Based on Visual Attention Mechanism Guidance Model in Unrestricted Posture. Scientific Programming. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1209254
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1209254