Face Hallucination Using Ensemble Face Synthesis

• Main Authors: Jang-Ren Luo, 羅章仁
• Other Authors: Ching-Ting Tu
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/s385e2

碩士 === 淡江大學 === 資訊工程學系資訊網路與通訊碩士班 === 102 === This study develops a face hallucination system based on a novel two-dimensional direct combined model (2DDCM) algorithm that employs a large collection of low-resolution/high-resolution facial pairwise training examples. This approach uses a formulation that directly combines the pairwise example in a 2D combined matrix while completely preserving the geometry-meaningful facial structures and the detailed facial features. Such a representation would be expected to yield a useful transformation for face reconstruction. Our algorithm achieves this goal by addressing four key issues. First, we establish the 2D combination representation that defines two structure-meaningful vector spaces to respectively describe the vertical and the horizontal facial-geometry properties. Second, we directly combine the low-resolution and high-resolution pairwise examples to completely model their relationship, thereby preserving their significant features. Third, we develop an optimization framework that finds an optimal transformation to best reconstruct the given low-resolution input. The 2D combination representation makes the transformation more powerful than other approaches. Fourth, specific to our framework, we will appropriately apply the proposed 2DDCM algorithm for modeling global and local properties of the facial image. Our approach is demonstrated by extensive experiments with high-quality hallucinated faces.