Towards Spatio-Temporal Face Alignment in Unconstrained Conditions
| Autor: | Nacim Ihaddadene, Pierre Tirilly, Marius Bilasco, Chabane Djeraba, Romain Belmonte |
|---|---|
| Přispěvatelé: | Institut Supérieur de l'Electronique et du Numérique - Lille (ISEN-Lille), Institut supérieur de l'électronique et du numérique (ISEN)-Université catholique de Lille (UCL), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), FOX MIIRE (LIFL), Laboratoire d'Informatique Fondamentale de Lille (LIFL), Université de Lille, Sciences et Technologies-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Sciences et Technologies-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS), Université de Lille, Sciences et Technologies, Institut supérieur de l'électronique et du numérique (ISEN) |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Structure (mathematical logic)
Landmark Localization Face Alignment Computer science business.industry [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] Context (language use) Pattern recognition Unconstrained Conditions Image (mathematics) Task (project management) Spatio-Temporal Models Feature (computer vision) Video-based Face (geometry) Artificial intelligence business Face detection Temporal information |
| Zdroj: | VISAPP VISAPP, Jan 2018, Funchal, Portugal VISIGRAPP (4: VISAPP) |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
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