Face hallucination based on sparse local-pixel structure

Li, Yongchao, Cai, Cheng, Qiu, Guoping and Lam, Kin-Man (2014) Face hallucination based on sparse local-pixel structure. Pattern Recognition, 47 (3). pp. 1261-1270. ISSN 0031-3203

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In this paper, we propose a face-hallucination method, namely face hallucination based on sparse local-pixel structure. In our framework, a high resolution (HR) face is estimated from a single frame low resolution (LR) face with the help of the facial dataset. Unlike many existing face-hallucination methods such as the from local-pixel structure to global image super-resolution method (LPS-GIS) and the super-resolution through neighbor embedding, where the prior models are learned by employing the least-square methods, our framework aims to shape the prior model using sparse representation. Then this learned prior model is employed to guide the reconstruction process. Experiments show that our framework is very flexible, and achieves a competitive or even superior performance in terms of both reconstruction error and visual quality. Our method still exhibits an impressive ability to generate plausible HR facial images based on their sparse local structures.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/996604
Keywords: Face hallucination; Sparse local-pixel structure; Super-resolution; Sparse representation
Schools/Departments: University of Nottingham Ningbo China > Faculty of Science and Engineering > School of Computer Science
University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number: https://doi.org/10.1016/j.patcog.2013.09.012
Depositing User: QIU, Lulu
Date Deposited: 31 Jul 2018 08:48
Last Modified: 04 May 2020 20:15
URI: https://eprints.nottingham.ac.uk/id/eprint/53184

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