An Example-Based Face Hallucination Method for Single-Frame, Low-Resolution Facial Images

This paper proposes a face hallucination method for the reconstruction of high-resolution facial images from single-frame, low-resolution facial images. The proposed method has been derived from example-based hallucination methods and morphable face models. First, we propose a recursive error back-projection method to compensate for residual errors, and a region-based reconstruction method to preserve characteristics of local facial regions. Then, we define an extended morphable face model, in which an extended face is composed of the interpolated high-resolution face from a given low-resolution face, and its original high-resolution equivalent. Then, the extended face is separated into an extended shape and an extended texture. We performed various hallucination experiments using the MPI, XM2VTS, and KF databases, compared the reconstruction errors, structural similarity index, and recognition rates, and showed the effects of face detection errors and shape estimation errors. The enco...

• Type: Journal
• Year: 2008
• Where: TIP
• Authors: Jeong-Seon Park, Seong-Whan Lee
• Keywords: Facial Images, Hallucination Methods, Low-resolution Facial Images, TIP 2008