Method for subpixel disparity calculation
AssigneeGideon Brothers d.o.o.
InventorsNikola Banić, Kruno Lenac, Dario Ljubić, Luka Pevec
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Abstract
In a method for subpixel disparity calculation, image data for various images each representing a field of view of an input device is received by a processor, and the image data is applied to a machine learning model. The machine learning module uses the image data to compute an output representing calculated subpixel disparity between the various images. In an example of the method, the machine learning model is a neural network that produces accurate and reliable subpixel disparity estimation in real-time using synthetically generated data.
Claims16
A computer implemented method for processing image data, the method comprising:
- providing one or more processors;
- configuring the one or more processors to receive first image data for a first image of a field of view and second image data for a second image of the field of view;
- configuring the one or more processors to apply the first image data and the second image data to a machine learning model, wherein the machine learning model is a neural network;
- configuring the one or more processors to compute, by the machine learning model, an output number that represents a calculated subpixel disparity between the first image and the second image;
- and
- configuring the one or more processors to train the neural network with synthetic data,
- wherein the synthetic data comprises one or more synthetically generated pairs of the first image and the second image, each pair of said one or more synthetically generated pairs comprising a predetermined subpixel disparity between the first image and the second image.
A system for processing image data, the system comprising:
- one or more processors;
- a non-transitory, computer readable medium, configured with instructions that, when executed by the one or more processors, cause the system to implement a neural network comprising an input layer configured to receive first image data for a first image of a field of view and second image data for a second image of the field of view;
- wherein the neural network is configured to provide an output number that represents a calculated subpixel disparity between the first image and the second image;
- and
- wherein the one or more processors are configured to train the neural network with synthetically generated data comprising one or more synthetically generated pairs of the first image and the second image, each pair of said one or more synthetically generated pairs comprising a predetermined subpixel disparity between the first image and the second image.
Dependencies are inferred from the claim text.