Fast and accurate head pose estimation via random projection forests

Donghoon Lee, Ming Hsuan Yang, Songhwai Oh

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

19 Citations (Scopus)

Abstract

In this paper, we consider the problem of estimating the gaze direction of a person from a low-resolution image. Under this condition, reliably extracting facial features is very difficult. We propose a novel head pose estimation algorithm based on compressive sensing. Head image patches are mapped to a large feature space using the proposed extensive, yet efficient filter bank. The filter bank is designed to generate sparse responses of color and gradient information, which can be compressed using random projection, and classified by a random forest. Extensive experiments on challenging datasets show that the proposed algorithm performs favorably against the state-of-the-art methods on head pose estimation in low-resolution images degraded by noise, occlusion, and blurring.

Original languageEnglish
Title of host publication2015 International Conference on Computer Vision, ICCV 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1958-1966
Number of pages9
ISBN (Electronic)9781467383912
DOIs
Publication statusPublished - 2015 Feb 17
Event15th IEEE International Conference on Computer Vision, ICCV 2015 - Santiago, Chile
Duration: 2015 Dec 112015 Dec 18

Publication series

NameProceedings of the IEEE International Conference on Computer Vision
Volume2015 International Conference on Computer Vision, ICCV 2015
ISSN (Print)1550-5499

Other

Other15th IEEE International Conference on Computer Vision, ICCV 2015
CountryChile
CitySantiago
Period15/12/1115/12/18

Fingerprint

Filter banks
Image resolution
Color
Experiments

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition

Cite this

Lee, D., Yang, M. H., & Oh, S. (2015). Fast and accurate head pose estimation via random projection forests. In 2015 International Conference on Computer Vision, ICCV 2015 (pp. 1958-1966). [7410584] (Proceedings of the IEEE International Conference on Computer Vision; Vol. 2015 International Conference on Computer Vision, ICCV 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCV.2015.227
Lee, Donghoon ; Yang, Ming Hsuan ; Oh, Songhwai. / Fast and accurate head pose estimation via random projection forests. 2015 International Conference on Computer Vision, ICCV 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 1958-1966 (Proceedings of the IEEE International Conference on Computer Vision).
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Lee, D, Yang, MH & Oh, S 2015, Fast and accurate head pose estimation via random projection forests. in 2015 International Conference on Computer Vision, ICCV 2015., 7410584, Proceedings of the IEEE International Conference on Computer Vision, vol. 2015 International Conference on Computer Vision, ICCV 2015, Institute of Electrical and Electronics Engineers Inc., pp. 1958-1966, 15th IEEE International Conference on Computer Vision, ICCV 2015, Santiago, Chile, 15/12/11. https://doi.org/10.1109/ICCV.2015.227

Fast and accurate head pose estimation via random projection forests. / Lee, Donghoon; Yang, Ming Hsuan; Oh, Songhwai.

2015 International Conference on Computer Vision, ICCV 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 1958-1966 7410584 (Proceedings of the IEEE International Conference on Computer Vision; Vol. 2015 International Conference on Computer Vision, ICCV 2015).

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

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Lee D, Yang MH, Oh S. Fast and accurate head pose estimation via random projection forests. In 2015 International Conference on Computer Vision, ICCV 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 1958-1966. 7410584. (Proceedings of the IEEE International Conference on Computer Vision). https://doi.org/10.1109/ICCV.2015.227