Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-37484-5_24
Title: Face hallucination on personal photo albums
Authors: Loke, Y.R.
Tan, P. 
Kassim, A.A. 
Issue Date: 2013
Source: Loke, Y.R.,Tan, P.,Kassim, A.A. (2013). Face hallucination on personal photo albums. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7729 LNCS (PART 2) : 284-295. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-37484-5_24
Abstract: This paper presents a new approach to generate a high quality facial image from a low resolution facial image, based on a large set of facial images belongs to the same person but varies in pose and expression. The input images are taken by low-end cameras or cameras from a long distance. The facial poses and expressions are not consistent and aligned. Firstly, using a low resolution facial image as a query image, a set of high resolution images with similar pose and expression is retrieved from the image examples by the proposed similarity measurement based on its shape and texture information of the query image. The selected images are then aligned with the query image and used as the candidates for the face hallucination. A Markov random field (MRF) model based on a new proposed color and edge constraints is introduced to find an optimum solution for the hallucination image. In the experiments, high textural details of hallucination images which are four to eight times larger than the original low resolution images were generated by the proposed face hallucination approach. The high resolution outputs of our method are significantly improved in quality compared to other image superresolution methods. Moreover, we also showed that our new approach is able to handle underexposure and noisy images. © 2013 Springer-Verlag.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/70286
ISBN: 9783642374838
ISSN: 03029743
DOI: 10.1007/978-3-642-37484-5_24
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