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Patent

Depth sensing camera systems and methods

Yishay Netzer
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TLDR
In this article, an inverse-square law relating the incident brightness on an area illuminated by a light point source, to its distance from the point source was proposed to estimate the depth and illuminance of a scene.
Abstract
This invention relates to a method and apparatus for sensing a three-dimensional (depth and illuminance) image of a scene It is based on the inverse-square law relating the incident brightness on an area illuminated by a light point source, to its distance from the point source In the preferred embodiment of the invention the scene is sequentially illuminated by more than one light point source each at a pre calibrated location in the reference coordinate system The resulting reflections from the field of-view are sensed by a stationary digital camera that maps each scene element into a corresponding image pixel, to provide a 2-dimensional brightness map that contains the photometric values of each image pixel for each specific illumination Each pixel photometric value depends on the illumination incident on the corresponding scene element which, in itself, is further determined by the element inherent Lambertian reflectance-coefficient at the illumination wavelength, the element orientation relative to the coordinate system, and the element illuminance as determined by the point source brightness and the distance separating the point source and the scene element Each brightness map is different from its sequel due to the differing point-source locations By manipulating the brightness maps the spatial location of each scene element relative to the fixed point sources is determined, thus yielding a depth-image as well as a brightness-image

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Citations
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References
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TL;DR: In this article, a non-contact sensor system consisting of a pattern generator to produce a 1×N array of time/space coded light rays, a linear array camera to image subsets of the light rays incident on the object surface, and a high speed range processor to determine depth by analyzing one-dimensional scan signals is described.
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