MFDNet: Collaborative Poses Perception and Matrix Fisher Distribution for Head Pose Estimation
| العنوان: | MFDNet: Collaborative Poses Perception and Matrix Fisher Distribution for Head Pose Estimation |
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| المؤلفون: | Jiazhang Wang, Shuai Fang, Duantengchuan Li, Ke Lin, Zhaoli Zhang, Hai Liu |
| المصدر: | IEEE Transactions on Multimedia. 24:2449-2460 |
| بيانات النشر: | Institute of Electrical and Electronics Engineers (IEEE), 2022. |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | Computer science, Probability density function, Rotation matrix, Computer Science Applications, Euler angles, Matrix (mathematics), symbols.namesake, Signal Processing, Metric (mathematics), Singular value decomposition, Media Technology, symbols, Electrical and Electronic Engineering, Quaternion, Algorithm, Pose |
| الوصف: | Head pose estimation suffers from several problems, including low pose tolerance under different disturbances and ambiguity arising from common head pose representation. In this study, a robust three-branch model with triplet module and matrix Fisher distribution module is proposed to address these problems. Based on metric learning, the triplet module employs triplet architecture and triplet loss. It is implemented to maximize the distance between embeddings with different pose pairs and minimize the distance between embeddings with same pose pairs. It can learn a highly discriminate and robust embedding related to head pose. Moreover, the rotation matrix instead of Euler angle and unit quaternion is utilized to represent head pose. An exponential probability density model based on the rotation matrix (referred to as the matrix Fisher distribution) is developed to model head rotation uncertainty. The matrix Fisher distribution can further analyze the head pose, and its maximum likelihood obtained using singular value decomposition provides enhanced accuracy. Extensive experiments executed over AFLW2000 and BIWI datasets demonstrate that the proposed model achieves state-of-the-art performance in comparison with traditional methods. |
| تدمد: | 1941-0077 1520-9210 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::ad380496f754d45656635ae3ad6f462b https://doi.org/10.1109/tmm.2021.3081873 |
| حقوق: | CLOSED |
| رقم الأكسشن: | edsair.doi...........ad380496f754d45656635ae3ad6f462b |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 19410077 15209210 |
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