Abstract:
Accurate face alignment is a vital step for most face perception tasks. In this paper, we proposed a new approach based on improved face shape searching for face alignmen...Show MoreMetadata
Abstract:
Accurate face alignment is a vital step for most face perception tasks. In this paper, we proposed a new approach based on improved face shape searching for face alignment. It begins with a shape space that contains diverse shapes. Unlike previous shape searching method that processes its every shape searching in the whole sample space, our method first train the random forest classifiers by training samples and partition the whole shape space into multiple sub-spaces, and then we process our shape searching in sub-spaces. Finally, we employ cascaded regression to achieve face alignment. Our method demonstrates its obvious decreases in searching time and its good robustness in unconstrained environment on three challenging datasets.
Published in: 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)
Date of Conference: 29-31 July 2017
Date Added to IEEE Xplore: 25 June 2018
ISBN Information: