Points of view generation allows to create virtual views between two or more cameras observing a scene. This field receives attention from multimedia markets, because sufficiently realistic points of view generation should allow to navigate freely between otherwise fixed points of observation. The new views must be interpolated between sampled data, aided by geometrical information relating real cameras poses, objects in the scene and desired point of view. Normally there are several steps involved, globally known as Structure from Motion (SfM) method. Our study focuses on the last stage; image interpolation based on the disparities between known cameras. In this paper, a new method is proposed that uses depth maps generated by a single camera, named SEBI, allowing a more efficient filling in presence of occlusions. Occlusions are considered during interpolation, creating an occlusion-map and an uncertainty-map using the depth information that SEBI cameras provide.
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