Face hallucination in a single modality environment has been heavily studied, in real-world environments under multiple modalities is still in its early stage. This paper presents a unified framework to solve face hallucination problem across multiple modalities i.e. different expressions, poses, illuminations. Almost all of the state-of-the-art face superresolution methods only generate a single output with the same modality of the low-resolution input. Our proposed framework is able to generate multiple outputs of different new modalities from only a single low-resolution input. It includes a global transformation with diagonal loading for modeling the mappings among different new facial modalities, and a local position-patch based method with weights compensation for incorporating image details. Experimental results illustrate the superiority of our framework.

Date Published: 14 February 2015
PDF: 5 pages
Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 94451T (14 February 2015); doi: 10.1117/12.2180572

Published in SPIE Proceedings Vol. 9445:
Seventh International Conference on Machine Vision (ICMV 2014)
Antanas Verikas; Branislav Vuksanovic; Petia Radeva; Jianhong Zhou, Editor(s)