Tongxuan Gao
ABSTRACT
Face alignment, as an important part of facial tasks, will affect the final efficiency and accuracy. Face alignment is to locate the exact shape of a detected face bounding box. There are amount of challenges in face alignment because of large poses, occlusions and illuminations in real-world conditions. The approaches to tackle these challenges can be categorized in methods based on regression, which require operators in feature extraction, and methods based on deep learning, in which the feature extraction is data driven.
Methods applies regression include Supervised Descent Method and Face Alignment by Coarse-to-Fine Shape Searching. Deep Convolutional Neural Networks, Tasks-Constrained Deep Convolutional Network and Multi-task Cascaded Convolutional Networks apply cascaded CNN and they are representational approaches of deep learning method. This article is devoted to the elaboration and summary of these mainstream methods.
- Cunjian Chen, Antitza Dantcheva, and Arun Ross. 2013. Automatic facial makeup detection with application in face recognition. Proc. - 2013 Int. Conf. Biometrics, ICB 2013 June (2013). DOI:https://doi.org/10.1109/ICB.2013.6612994Google Scholar
Cross Ref
- Huiyu Mo, Leibo Liu, Wenping Zhu, Shouyi Yin, and Shaojun Wei. 2018. Face Alignment With Expression- and Pose-Based Adaptive Initialization. IEEE Trans. Multimed. PP, (August 2018), 1. DOI:https://doi.org/10.1109/TMM.2018.2867262Google Scholar
- Jiuxiang Gu, Zhenhua Wang, Jason Kuen, Lianyang Ma, Amir Shahroudy, Bing Shuai, Ting Liu, Xingxing Wang, Gang Wang, Jianfei Cai, and Tsuhan Chen. 2018. Recent advances in convolutional neural networks. Pattern Recognit. 77, (2018), 354–377. DOI:https://doi.org/10.1016/j.patcog.2017.10.013Google ScholarDigital Library
- Yi Sun, Xiaogang Wang, and Xiaoou Tang. 2013. Deep convolutional network cascade for facial point detection. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 3476–3483. DOI:https://doi.org/10.1109/CVPR.2013.446Google ScholarDigital Library
- George Trigeorgis, Patrick Snape, Mihalis A. Nicolaou, Epameinondas Antonakos, and Stefanos Zafeiriou. 2016. Mnemonic Descent Method: A Recurrent Process Applied for End-to-End Face Alignment. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 4177–4187. DOI:https://doi.org/10.1109/CVPR.2016.453Google ScholarCross Ref
- Xuehan Xiong and Fernando De La Torre. 2013. Supervised descent method and its applications to face alignment. Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. (2013), 532–539. DOI:https://doi.org/10.1109/CVPR.2013.75Google ScholarDigital Library
- Kaipeng Zhang, Zhanpeng Zhang, Zhifeng Li, and Yu Qiao. 2016. Joint Face Detection and Alignment using multi-task cascaded cnn.pdf. IEEE Signal Process. Lett. 23, 10 (2016), 1499–1503. DOI:https://doi.org/10.1109/lsp.2016.2603342Google ScholarCross Ref
- Zhanpeng Zhang, Ping Luo, Chen Change Loy, and Xiaoou Tang. 2014. Facial landmark detection by deep multi-task learning. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 8694 LNCS, 94–108. DOI:https://doi.org/10.1007/978-3-319-10599-4_7Google Scholar
- Shizhan Zhu, Cheng Li, Chen Change Loy, and Xiaoou Tang. 2015. Face alignment by coarse-to-fine shape searching. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition 07-12-June, 4998–5006. DOI:https://doi.org/10.1109/CVPR.2015.7299134Google Scholar
Index Terms
- A Survey for Conventional Regression- and Deep Learning-based Face Alignment Methods
Recommendations
A survey on deep learning based face recognition
AbstractDeep learning, in particular the deep convolutional neural networks, has received increasing interests in face recognition recently, and a number of deep learning methods have been proposed. This paper summarizes about 330 ...
Graphical abstractDisplay Omitted
Highlights- Presents a comprehensive survey of deep learning based face recognition methods.
Face Recognition Based on Deep Learning
Human Centered ComputingAbstractAs one of the non-contact biometrics, face representation had been widely used in many circumstances. However conventional methods could no longer satisfy the demand at present, due to its low recognition accuracy and restrictions of many ...
Robust face alignment by cascaded regression and de-occlusion
AbstractFace alignment is a typical facial behavior analysis task in computer vision. However, the performance of face alignment is degraded greatly when the face image is partially occluded. In order to achieve better mapping between facial ...
Highlights- A novel algorithm called CRD is proposed to seamlessly integrate face de-occlusion module and deep regression module into a cascaded deep generative ...
Comments