Literature DB >> 15376880

Automatic eyeglasses removal from face images.

Chenyu Wu1, Ce Liu, Heung-Yueng Shum, Ying-Qing Xu, Zhengyou Zhang.   

Abstract

In this paper, we present an intelligent image editing and face synthesis system that automatically removes eyeglasses from an input frontal face image. Although conventional image editing tools can be used to remove eyeglasses by pixel-level editing, filling in the deleted eyeglasses region with the right content is a difficult problem. Our approach works at the object level where the eyeglasses are automatically located, removed as one piece, and the void region filled. Our system consists of three parts: eyeglasses detection, eyeglasses localization, and eyeglasses removal. First, an eye region detector, trained offline, is used to approximately locate the region of eyes, thus the region of eyeglasses. A Markov-chain Monte Carlo method is then used to accurately locate key points on the eyeglasses frame by searching for the global optimum of the posterior. Subsequently, a novel sample-based approach is used to synthesize the face image without the eyeglasses. Specifically, we adopt a statistical analysis and synthesis approach to learn the mapping between pairs of face images with and without eyeglasses from a database. Extensive experiments demonstrate that our system effectively removes eyeglasses.

Mesh:

Year:  2004        PMID: 15376880     DOI: 10.1109/TPAMI.2004.1262319

Source DB:  PubMed          Journal:  IEEE Trans Pattern Anal Mach Intell        ISSN: 0098-5589            Impact factor:   6.226


  2 in total

1.  Eyeglasses lens contour extraction from facial images using an efficient shape description.

Authors:  Diana Borza; Adrian Sergiu Darabant; Radu Danescu
Journal:  Sensors (Basel)       Date:  2013-10-10       Impact factor: 3.576

2.  Image based hair segmentation algorithm for the application of automatic facial caricature synthesis.

Authors:  Yehu Shen; Zhenyun Peng; Yaohui Zhang
Journal:  ScientificWorldJournal       Date:  2014-01-29
  2 in total

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