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Optical Engineering • Open Access

Using gradient-based ray and candidate shadow maps for environmental illumination distribution estimation
Author(s): Changkyoung Eem; Iksu Kim; Hyunki Hong

Paper Abstract

A method to estimate the environmental illumination distribution of a scene with gradient-based ray and candidate shadow maps is presented. In the shadow segmentation stage, we apply a Canny edge detector to the shadowed image by using a three-dimensional (3-D) augmented reality (AR) marker of a known size and shape. Then the hierarchical tree of the connected edge components representing the topological relation is constructed, and the connected components are merged, taking their hierarchical structures into consideration. A gradient-based ray that is perpendicular to the gradient of the edge pixel in the shadow image can be used to extract the shadow regions. In the light source detection stage, shadow regions with both a 3-D AR marker and the light sources are partitioned into candidate shadow maps. A simple logic operation between each candidate shadow map and the segmented shadow is used to efficiently compute the area ratio between them. The proposed method successively extracts the main light sources according to their relative contributions on the segmented shadows. The proposed method can reduce unwanted effects due to the sampling positions in the shadow region and the threshold values in the shadow edge detection.

Paper Details

Date Published: 24 July 2015
PDF: 8 pages
Opt. Eng. 54(7) 073112 doi: 10.1117/1.OE.54.7.073112
Published in: Optical Engineering Volume 54, Issue 7
Show Author Affiliations
Changkyoung Eem, Chung-Ang Univ. (Korea, Republic of)
Iksu Kim, Chung-Ang Univ. (Korea, Republic of)
Hyunki Hong, Chung-Ang Univ. (Korea, Republic of)

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