Robust frontal view search using multi-camera constrained Isomap

Chao Wang, Xubo Song

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Many 2D face processing algorithms can perform better using frontal or near frontal face. In this paper, we present a robust frontal view search method, and apply it to a scene where a rotating head is simultaneously captured by multiple cameras. Our method is based on manifold embedding using Isomap, with the assumption that with head pose being the only variable, the face images should lie in a smooth and low dimensional manifold. We constrain Isomap by (1) a spatio-temporal constraint which improves the neighborhood graph of Isomap to make the manifold retain smooth and low-dimensional under uncontrolled conditions; (2) a multi-camera constraint which reflects the relative pose of multiple simultaneous video streams to adjust the graph distance of manifold in iteration. Using the constrained Isomap, the frontal view is in the vertex of the parabola-shaped manifold in 2D embedding. The experiments show that the results have high reliability.

Original languageEnglish (US)
Title of host publication2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
Pages1017-1020
Number of pages4
DOIs
StatePublished - Dec 1 2012
Event2012 19th IEEE International Conference on Image Processing, ICIP 2012 - Lake Buena Vista, FL, United States
Duration: Sep 30 2012Oct 3 2012

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2012 19th IEEE International Conference on Image Processing, ICIP 2012
CountryUnited States
CityLake Buena Vista, FL
Period9/30/1210/3/12

Keywords

  • Frontal view search
  • Isomap
  • manifold learning
  • multi-camera
  • spatio-temporal

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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