Estimating Lighting and Geometry Information from Time-Lapse Videos via Non-Negative Matrix Factorization
نویسندگان
چکیده
To create appealing realistic visual effects, complete geometric models, lightings, and material properties of a scene are often required in film production or augmented reality. This compact representation also enables various applications in many image synthesis and editing tasks. In this paper, we introduce an iterative photometric stereo approach via non-negative matrix factorization (NMF) to model an outdoor scene from a time-lapse video, and retrieve the surface geometry and lighting information of the scene even in the presence of shadow. To accomplish this, in this paper, we provide 1) a novel shadow detection method to locate shadow pixels in a time-lapse video, and 2) an iterative photometric stereo framework with NMF to recover the geometry and lighting information of the outdoor scene.
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