Statistical multiple light source detection

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Statistical multiple light source detection

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Multiple light source detection has many applications in image synthesis and augmented reality. Current techniques can provide accurate results but have limited applicability in real-life scenarios where interaction with the scene is not possible. The authors provide a statistical framework for multiple light source detection that relies on the common features of objects belonging to a particular class and illustrate it using the class of human faces. Experiments with real data demonstrate that a light distribution with up to three light sources can be detected within 13° mean error. Application of the proposed framework to the problem of 3D reconstruction from multiple images under arbitrary lighting demonstrates the effectiveness of the framework compared with current techniques.

Inspec keywords: image reconstruction; augmented reality

Other keywords: image synthesis; augmented reality; 3D reconstruction; statistical multiple light source detection

Subjects: Computer vision and image processing techniques; Virtual reality; Optical, image and video signal processing

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