Integration of precise iris localization into active appearance models for automatic initialization and robust deformable face tracking
Sebastian Vater, Ralph Ivancevic, Fernando Puente León · 2017
Face tracking and facial landmarking plays an important role in human-machine interaction. Active-Appearance Models (AAM) represent a well-established method to mathematically describe face characteristics such as facial expression and attentiveness. However, the applicability of AAM suffers from their high sensitivity to initialization and low robustness in scenarios of strong head movements. We show how a robust, automatic initialization of AAM can be performed by integration of precise iris localization into the AAM fitting algorithm. The shape and global transform parameters are extracted from the re-initialized model to provide well-suited start parameters for the subsequent fitting. The method is validated on the gi4e database showing an improvement to naive initialization and re-initialization in terms of robustness and accuracy.