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Subject: search.filters.subject.Light source estimation

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    Near light source location estimation using illumination of a diffused planar background
    (2014-11-10)
    Chotikakamthorn, Nopporn
    The problem of light source location estimation is considered. It is shown that the location of a near light source can be estimated from an optical-depth image pair using information available from an illuminated Lambertian planar background. The method estimates the projected source location on the planar background from the surface illumination gradient. The distance of the light source from the planar background, which is equivalent to its elevation angle, is estimated by fitting the radiance of the background surface as observed by an optical image, with those synthesized at different light distances. The fitting equation is formulated such that the possible existence of environment light can be taken into account. Experimental results with real images are provided.
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    Weighted hough transform for directional light sources estimation from multi-view images
    (2012-12-01)
    Bunteong, Anusorn
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    Chotikakamthorn, Nopporn
    An improved method for light sources estimation from shading is proposed in this paper. This method indicates the advantage of multi-view images rather than single view image. Even though there are several methods that can be used to estimate light sources from single view image, data from single view may be not accurate for all light source estimations. The shading on a Lambertian surface sphere is used to detection critical paths and the directions of directional light sources can be estimated from these paths. Hough Transform is used to find critical paths from critical points in images. Rather than using the standard Hough Transform, we improve vote count processes by determining a weight value for each critical point in Hough space. Weight values are calculated from angles between surface normal at each critical point and view vector from cameras. The experimental results demonstrate that the proposed method with information obtained from multi-view images yields better performance than the method with a single-view image.