On Constructing Facial Similarity Maps

Automatically determining facial similarity is a difficult and open question in computer vision. The problem is complicated both because it is unclear what facial features humans use to determine facial similarity and because facial similarity is subjective in nature: similarity judgements change from person to person. In this work we suggest a system which places facial similarity on a solid computational footing. First we describe methods for acquiring facial similarity ratings from humans in an efficient manner. Next we show how to create feature vector representations for each face by extracted patches around facial keypoints. Finally we show how to use the acquired similarity ratings to learn functional mapping which project facialfeature vectors into Face Spaces which correspond to our notions of facial similarity. We use different collections of images to both create and validate the Face Spaces including: perceptual similarity data obtained from humans, morphed faces between t...

• Type: Conference
• Year: 2007
• Where: CVPR
• Authors: Alex Holub, Yun-hsueh Liu, Pietro Perona
• Keywords: Computer Vision, CVPR 2007, Facial Features Humans, Facial Similarity, Facial Similarity Ratings, Perceptual Similarity Data, Similarity Judgements