Abstract

We address the issues of 3-D head pose estimation and face modeling from a depth image. Given a depth image, random forests are effective for estimating the location and orientation of a person's head. However, the accuracy of the estimation is not high enough. We propose using corrected regression votes. The corrected votes are obtained by considering the cooperation of all trees, leading to significant improvement of head pose estimation accuracy. Based on the head pose estimator, we present a face modeling system. In our system, the face model is generated by aligning a deformable face model to a depth image using an iterative closest point (ICP) algorithm. The novelty of our approach is that an optimal weight for each vertex is incorporated into the ICP algorithm with point to plane constraints. Experiments show that our system can automatically estimate the head pose and generate a realistic face model from a single depth image. We also provide a detailed evaluation that shows the benefits of our approach.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.