Multi-view face hallucination based on sparse representation

Zhuo Hui, Kin Man Lam

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)

Abstract

In this paper, we propose a novel method to generate the hallucinated multi-views of faces using the sparse-representation model. In order to render a faithful virtual view, we introduce centralized constraints into a variation framework for optimization. The constraints are formulated based on an attempt to minimize the difference between the sparse-coding coefficients derived for two distinct views. In our algorithm, sift optical-flow method is employed to formulate the constraints. An input face is firstly sparsely coded over a given dictionary, and then the sparse-coding coefficients for the input face are refined through an optimization framework with the centralized constraints. Intensive experimental results demonstrate that our proposed method can perform well in terms of both reconstruction accuracy and visual quality..
Original languageEnglish
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages2202-2206
Number of pages5
DOIs
Publication statusPublished - 18 Oct 2013
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: 26 May 201331 May 2013

Conference

Conference2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Country/TerritoryCanada
CityVancouver, BC
Period26/05/1331/05/13

Keywords

  • Face Hallucination
  • Multi-view
  • Sparse Representation

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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