What characterizes a shadow boundary under the sun and sky?

Xiang Huang*, Gang Hua, Jack Tumblin, Lance Williams

*Corresponding author for this work

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

30 Scopus citations

Abstract

Despite decades of study, robust shadow detection remains difficult, especially within a single color image. We describe a new approach to detect shadow boundaries in images of outdoor scenes lit only by the sun and sky. The method first extracts visual features of candidate edges that are motivated by physical models of illumination and occluders. We feed these features into a Support Vector Machine (SVM) that was trained to discriminate between most-likely shadow-edge candidates and less-likely ones. Finally, we connect edges to help reject non-shadow edge candidates, and to encourage closed, connected shadow boundaries. On benchmark shadow-edge data sets from Lalonde et al. and Zhu et al., our method showed substantial improvements when compared to other recent shadow-detection methods based on statistical learning.

Original languageEnglish (US)
Title of host publication2011 International Conference on Computer Vision, ICCV 2011
Pages898-905
Number of pages8
DOIs
StatePublished - Dec 1 2011
Event2011 IEEE International Conference on Computer Vision, ICCV 2011 - Barcelona, Spain
Duration: Nov 6 2011Nov 13 2011

Publication series

NameProceedings of the IEEE International Conference on Computer Vision

Other

Other2011 IEEE International Conference on Computer Vision, ICCV 2011
CountrySpain
CityBarcelona
Period11/6/1111/13/11

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'What characterizes a shadow boundary under the sun and sky?'. Together they form a unique fingerprint.

  • Cite this

    Huang, X., Hua, G., Tumblin, J., & Williams, L. (2011). What characterizes a shadow boundary under the sun and sky? In 2011 International Conference on Computer Vision, ICCV 2011 (pp. 898-905). [6126331] (Proceedings of the IEEE International Conference on Computer Vision). https://doi.org/10.1109/ICCV.2011.6126331