Densely tracking sequences of 3D face scans

TL;DR

This paper introduces a new method for densely tracking sequences of 3D face scans by extending the non-rigid ICP algorithm with a temporal criterion, improving accuracy over existing methods.

Contribution

It presents a novel fitting framework that automatically tracks full 3D face scan sequences, incorporating temporal information for enhanced dense tracking accuracy.

Findings

Outperforms state-of-the-art algorithms on BU4D-FE database

Demonstrates improved dense tracking accuracy

Validates effectiveness of temporal extension

Abstract

3D face dense tracking aims to find dense inter-frame correspondences in a sequence of 3D face scans and constitutes a powerful tool for many face analysis tasks, e.g., 3D dynamic facial expression analysis. The majority of the existing methods just fit a 3D face surface or model to a 3D target surface without considering temporal information between frames. In this paper, we propose a novel method for densely tracking sequences of 3D face scans, which ex- tends the non-rigid ICP algorithm by adding a novel specific criterion for temporal information. A novel fitting framework is presented for automatically tracking a full sequence of 3D face scans. The results of experiments carried out on the BU4D-FE database are promising, showing that the proposed algorithm outperforms state-of-the-art algorithms for 3D face dense tracking.