I3B - Institute for Research and Innovation in Bioengineering, Universitat Politècnica de València, Valencia, Spain.
PLoS One. 2019 Jan 29;14(1):e0211314. doi: 10.1371/journal.pone.0211314. eCollection 2019.
Classification or typology systems used to categorize different human body parts have existed for many years. Nevertheless, there are very few taxonomies of facial features. Ergonomics, forensic anthropology, crime prevention or new human-machine interaction systems and online activities, like e-commerce, e-learning, games, dating or social networks, are fields in which classifications of facial features are useful, for example, to create digital interlocutors that optimize the interactions between human and machines. However, classifying isolated facial features is difficult for human observers. Previous works reported low inter-observer and intra-observer agreement in the evaluation of facial features. This work presents a computer-based procedure to automatically classify facial features based on their global appearance. This procedure deals with the difficulties associated with classifying features using judgements from human observers, and facilitates the development of taxonomies of facial features. Taxonomies obtained through this procedure are presented for eyes, mouths and noses.
多年来，用于对人体不同部位进行分类或分类的系统已经存在。然而，面部特征的分类系统却很少。人体工程学、法医人类学、犯罪预防或新的人机交互系统以及在线活动，如电子商务、在线学习、游戏、约会或社交网络，都是有用的分类系统的领域，例如，创建优化人机交互的数字对话者。然而，人类观察者很难对孤立的面部特征进行分类。以前的工作报道了在评估面部特征时观察者之间的低一致性和一致性。本工作提出了一种基于全局外观自动分类面部特征的计算机方法。该方法解决了使用人类观察者的判断进行特征分类所带来的困难，并促进了面部特征分类法的发展。本文提出了基于该方法获得的眼睛、嘴和鼻子的分类法。
