Facial Landmark Localization in Depth Images Using Supervised Ridge Descent
15th IEEE International Conference on Computer Vision Workshops, ICCVW 2015, Santiago, Şili, 11 - 18 Aralık 2015, cilt.2015-February, ss.378-383, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Cilt numarası: 2015-February
- Doi Numarası: 10.1109/iccvw.2015.57
- Basıldığı Şehir: Santiago
- Basıldığı Ülke: Şili
- Sayfa Sayıları: ss.378-383
- Anahtar Kelimeler: Databases, Face, Feature extraction, Nose, Shape, Three-dimensional displays, Training
- Boğaziçi Üniversitesi Adresli: Evet
Özet
Supervised Descent Method (SDM) has proven successful in many computer vision applications such as face alignment, tracking and camera calibration. Recent studies which used SDM, achieved state of the-art performance on facial landmark localization in depth images [4]. In this study, we propose to use ridge regression instead of least squares regression for learning the SDM, and to change feature sizes in each iteration, effectively turning the landmark search into a coarse to fine process. We apply the proposed method to facial landmark localization on the Bosphorus 3D Face Database, using frontal depth images with no occlusion. Experimental results confirm that both ridge regression and using adaptive feature sizes improve the localization accuracy considerably.