Canonical Face Depth mAP: A Robust 3D Representation for Face Verification

Abstract

The canonical face depth map (CFDM) is a standardized representation for storing and manipulating 3D data from human faces. Our algorithm automates the process of transforming a 3D face scan into its canonical representation, eliminating the need for hand-labeled anchor points. The presented algorithm is designed to be a robust, fully automatic preprocessor for any 3D face recognition algorithm. The experimental results presented here demonstrate that our CFDM is robust to noise and occlusion, and we show that using such a canonical representation can improve the efficiency efface recognition algorithms and reduce memory requirements. Producing the CFDM takes, on average, 0.85 seconds for 320 times 240 pixel scans, and 3.8 seconds for 640 times 480 pixel scans (using a dual AMD Opteron 275, 2.2 GHz, with 2 MB Cache, and 1 GIG RAM). The CFDM enables both 2D and 3D image processing methods - such as convolution and PCA - to be readily used for feature localization and face recognition.