Patent 10121055 was granted and assigned to Carnegie Mellon University on November, 2018 by the United States Patent and Trademark Office.
This invention describes methods and systems for the automated facial landmark localization. Our approach proceeds from sparse to dense landmarking steps using a set of models to best account for the shape and texture variation manifested by facial landmarks across pose and expression. We also describe the use of an l1-regularized least squares approach that we incorporate into our shape model, which is an improvement over the shape model used by several prior Active Shape Model (ASM) based facial landmark localization algorithms.