NDLI: Face alignment under occlusion based on local and global feature regression

Content Provider	Springer Nature Link
Author	Guo, Songrui Tan, Guanghua Pan, Huawei Chen, Lin Gao, Chunming
Copyright Year	2016
Abstract	Shape alignment or estimation under occlusion is one of the most challenging tasks in computer vision field. Most previous works treat occlusion as noises or part models, which usually lead to low accuracy or inefficiencies. This paper proposes an efficient and accurate regression-based algorithm for face alignment. In this framework, local and global regressions are iteratively used to train a series of random forests in a cascaded manner. In training and testing process, each step consists of two layers. In the first layer, a set of highly discriminative local features are extracted from local regions according to locality principle. The regression forests are trained for each facial landmark independently using those local features. Then the leaf node of the regression tree is encoded by histogram statistic method and the final shape is estimated by a linear regression matrix. In the second layer, our proposed global features are generated. Then we use those features to train a random fern to keep the global shape constraints. Experiments show that our method has a high speed, but same or slightly lower accuracy than state of the art methods under occlusion condition. In order to gain a higher accuracy we use multi-random shape for initialization, which may slightly reduce the calculation efficiency as a trade-off.
Starting Page	8677
Ending Page	8694
Page Count	18
File Format	PDF
ISSN	13807501
Journal	Multimedia Tools and Applications
Volume Number	76
Issue Number	6
e-ISSN	15737721
Language	English
Publisher	Springer US
Publisher Date	2016-04-11
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Occlusion Local regression Global regression Shape-indexed feature Face alignment Multimedia Information Systems Computer Communication Networks Data Structures, Cryptology and Information Theory Special Purpose and Application-Based Systems
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Hardware and Architecture Software Media Technology

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