Why Is Facial Occlusion a Challenging Problem
Hazim Kemal Ekenel,Rainer Stiefelhagen +1 more
- pp 299-308
TLDR
Improved alignment increases the correct recognition rate also in the experiments against the lower face occlusion, which shows that face registration plays a key role on face recognition performance.Abstract:
This paper investigates the main reason for the obtained low performance when the face recognition algorithms are tested on partially occluded face images. It has been observed that in the case of upper face occlusion, missing discriminative information due to occlusion only accounts for a very small part of the performance drop. The main factor is found to be the registration errors due to erroneous facial feature localization. It has been shown that by solving the misalignment problem, very high correct recognition rates can be achieved with a generic local appearance-based face recognition algorithm. In the case of a lower face occlusion, only a slight decrease in the performance is observed, when a local appearance-based face representation approach is used. This indicates the importance of local processing when dealing with partial face occlusion. Moreover, improved alignment increases the correct recognition rate also in the experiments against the lower face occlusion, which shows that face registration plays a key role on face recognition performance.read more
Citations
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Journal ArticleDOI
Facial Expression Analysis under Partial Occlusion: A Survey
TL;DR: A comprehensive review of recent advances in dataset creation, algorithm development, and investigations of the effects of occlusion critical for robust performance in FEA systems is presented in this paper.
Journal ArticleDOI
Partial Face Recognition: Alignment-Free Approach
TL;DR: It is argued that a probe face image, holistic or partial, can be sparsely represented by a large dictionary of gallery descriptors by adopting a variable-size description which represents each face with a set of keypoint descriptors.
Journal ArticleDOI
Facial Expression Analysis under Partial Occlusion: A Survey
TL;DR: A comprehensive review of recent advances in dataset creation, algorithm development, and investigations of the effects of occlusion critical for robust performance in FEA systems is presented in this article.
Journal ArticleDOI
Facial feature point detection: A comprehensive survey
TL;DR: A comprehensive survey of facial feature point detection with the assistance of abundant manually labeled images is presented in this article, where the authors categorize existing methods into two primary categories according to whether there is the need of a parametric shape model: Parametric Shape Model-based methods and Nonparametric Shape Models-Based methods.
Proceedings ArticleDOI
SURF-Face: Face Recognition Under Viewpoint Consistency Constraints.
TL;DR: Experimental results on the AR-Face and CMU-PIE database using manually aligned faces, unaligned faces, and partially occluded faces show that the proposed approach is robust and can outperform current generic approaches.
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