Detection of pose orientation across single and multiple axes in case of 3D face images

TL;DR

This paper introduces a new method for detecting the pose orientation of 3D face images across multiple axes, achieving up to 80% accuracy on several databases, which advances face pose recognition technology.

Contribution

The paper presents a novel algorithm capable of identifying 3D face pose across multiple axes with high accuracy, tested on multiple publicly available databases.

Findings

Achieved 67% correct pose recognition on FRAV3D database.

Achieved 80% correct pose recognition on GAVADB and Bosphorus databases.

Validated the method's effectiveness across diverse 3D face datasets.

Abstract

In this paper, we propose a new approach that takes as input a 3D face image across X, Y and Z axes as well as both Y and X axes and gives output as its pose i.e. it tells whether the face is oriented with respect the X, Y or Z axes or is it oriented across multiple axes with angles of rotation up to 42 degree. All the experiments have been performed on the FRAV3D, GAVADB and Bosphorus database which has two figures of each individual across multiple axes. After applying the proposed algorithm to the 3D facial surface from FRAV3D on 848 3D faces, 566 3D faces were correctly recognized for pose thus giving 67% of correct identification rate. We had experimented on 420 images from the GAVADB database, and only 336 images were detected for correct pose identification rate i.e. 80% and from Bosphorus database on 560 images only 448 images were detected for correct pose identification i.e. 80%.abstract goes here.