Performance Analysis of Point Light Source Estimation
نویسنده
چکیده
In this paper, the performance of point light source parameter estimation from two video images is analyzed in terms of estimation theory. The illumination parameters are the intensity and direction of a single distant point light source in presence of ambient light. Known illumination estimation methods evaluate temporal changing shading on the surface of rotating objects in two video images. Additionally, the methods evaluate the 3D shape and the motion of the moving objects in the image sequence. In this paper, all input data and its inherent errors are described by a stochas-tic observation model. Based on this model, illumination estimation is described as maximum likelihood estimation. The performance is analyzed regarding the Cram er-Rao theoretical lower bound of estimation error variances for a variety of cases of scene illumination , object motion and errors in input data. Finally, it is shown that the most recent estimator from the literature is not optimal in case of errors in shape or motion information. The presented theoretical framework give insights how to improve the estimator.
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