Facebook Technologies, LLC (Menlo Park, CA)
This disclosure generally refers to depth estimation derived from image data, and more specifically , to multi-channel depth estimation using census transforms.
A variety of headsets used in artificial reality systems typically have depth estimation systems. They can be used to determine the depth information of artificial real-world environments. The most common methods of getting depth information are based on stereo algorithms that establish a stereo correspondence between two images by considering visible light only using one luminance (luma) channel. But, stereo algorithms that are built on a luma channel are limited in instances where the lightchannel may have low contrast, e.g. when you are in the outdoors in a saturated environment with light or in a low-light environment.
The present disclosure is about how to determine depth information using a stereo pair images from two cameras attached to headset. The method involves taking one image at a first camera, and another at another camera (e.g. on a headset), the first and second images containing an environment, which is captured in multiple of light channels (e.g. some combination of red and green blue, infrared and red). The method also computes the census transform using at most two light channels of the plurality light channels for each pixels in the first image as well as each of the pixel in the second image. A depth map is created using the comparison of the census transformations in at least two lightchannels. Stereo algorithms are able to be utilized to generate the depth map. These algorithms calculate the stereo correlation between the first and second image by analyzing the census transforms that are in two lightchannels at minimum. A headset in an artificial reality environment that implements the method can generate virtual content that is displayed by an electronic display that displays the created depth map.Click here to view the patent on USPTO website.
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