Towards Spatio-temporal Face Alignment in Unconstrained Conditions

被引:0
|
作者
Belmonte, R. [1 ,3 ]
Ihaddadene, N. [1 ]
Tirilly, P. [2 ]
Bilasco, M. [3 ]
Djeraba, C. [2 ]
机构
[1] IISEN Lille, Yncrea Hauts De France, France
[2] Univ Lille, CNRS, Ctr Rech Informat Signal & Automat Lille, UMR 9189,IMT Lille Douai,CRIStAL,Cent Lille, F-59000 Lille, France
[3] Univ Lille, CNRS, Ctr Rech Informat Signal & Automat Lille, UMR 9189,CRIStAL,Cent Lille, F-59000 Lille, France
关键词
Face Alignment; Spatio-temporal Models; Landmark Localization; Video-based; Unconstrained Conditions; REPRESENTATION;
D O I
10.5220/0006651904330438
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Face alignment is an essential task for many applications. Its objective is to locate feature points on the face, in order to identify its geometric structure. Under unconstrained conditions, the different variations that may occur in the visual context, together with the instability of face detection, make it a difficult problem to solve. While many methods have been proposed, their performances under these constraints are still not satisfactory. In this article, we claim that face alignment should be studied using image sequences rather than still images, as it has been done so far. We show the importance of taking into consideration the temporal information under unconstrained conditions.
引用
收藏
页码:433 / 438
页数:6
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