Post-manufacture camera calibration
First Claim
1. A computer-implemented method comprising:
- receiving, at a computer server system from a mobile device, a first training image taken by a camera module of the mobile device and an image-context attribute describing a context associated with the first training image, wherein the image-context attribute is separate from the first training image;
adding, by the computer server system, the first training image into a sub-group of training images in accordance with a similarity based, at least in part, on the image-context attribute;
in response to determining that a training set of images including the sub-group provides a threshold amount of data samples to compute a calibration parameter model, computing, by the computer server system, the calibration parameter model based, at least in part, on the sub-group of training images utilizing dimension reduction statistical analysis, wherein the calibration parameter model configures at least an image adjustment process corresponding to the image-context attribute and wherein the image adjustment process is configured to define how to post-process a raw photograph after being captured by the camera module; and
causing, by the computer server system, an image processor to calibrate the raw photograph of the camera module by providing the calibration parameter model to the image processor.
2 Assignments
0 Petitions
Accused Products
Abstract
Some embodiments include a method of operating a calibration server for a camera module. The method can include: receiving, by the computing server, a first training image taken by the camera module in a mobile device and a corresponding image-context attribute from the mobile device; aggregating, by the computing device, the first training image into a set of contextually similar images based on the image-context attribute; computing a calibration parameter model based on the set of contextually similar images utilizing dimension reduction statistical analysis; and scheduling to update the calibration parameter model to configure an image processor to adjust a raw photograph of the camera module according to the calibration parameter model.
41 Citations
16 Claims
-
1. A computer-implemented method comprising:
-
receiving, at a computer server system from a mobile device, a first training image taken by a camera module of the mobile device and an image-context attribute describing a context associated with the first training image, wherein the image-context attribute is separate from the first training image; adding, by the computer server system, the first training image into a sub-group of training images in accordance with a similarity based, at least in part, on the image-context attribute; in response to determining that a training set of images including the sub-group provides a threshold amount of data samples to compute a calibration parameter model, computing, by the computer server system, the calibration parameter model based, at least in part, on the sub-group of training images utilizing dimension reduction statistical analysis, wherein the calibration parameter model configures at least an image adjustment process corresponding to the image-context attribute and wherein the image adjustment process is configured to define how to post-process a raw photograph after being captured by the camera module; and causing, by the computer server system, an image processor to calibrate the raw photograph of the camera module by providing the calibration parameter model to the image processor. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
-
-
9. A non-transitory computer-readable data storage medium storing computer-executable instructions that, when executed, cause a computer system to perform a computer-implemented method, the computer-executable instructions comprising:
-
instructions for receiving, at a computer server system from a mobile device, a first training image taken by a camera module of the mobile device and an image-context attribute describing a context associated with the first training image, wherein the image-context attribute is separate from the first training image; instructions for adding, by a computer server system, the first training image into a sub-group of training images in accordance with a similarity based, at least in part, on the image-context attribute; instructions for in response to determining that a training set of images including the sub-group provides a threshold amount of data samples to compute a calibration parameter model, computing, by the computer server system, the calibration parameter model based, at least in part, on the subgroup of training images utilizing dimension reduction statistical analysis, wherein the calibration parameter model configures at least an image adjustment process corresponding to the image-context attribute and wherein the image adjustment process is configured to define how to post-process a raw photograph after being captured by the camera module; and instructions for causing, by a computer server system, an image processor to calibrate the raw photograph of the camera module by providing the calibration parameter model to the image processor. - View Dependent Claims (10, 11, 12, 13, 14, 15)
-
-
16. A computer system, comprising:
-
a non-transitory memory device configured to store executable instructions; a processor configured by the executable instructions to; receive, from a mobile device, a first training image taken by a camera module of the mobile device and an image-context attribute describing a context associated with the first training image, wherein the image-context attribute is separate from the first training image; add the first training image into a sub-group of training images in accordance with a similarity based, at least in part, on the image-context attribute; in response to determining that a training set of images including the sub-group provides a threshold amount of data samples to compute a calibration parameter model, compute the calibration parameter model based, at least in part, on the sub-group of training images utilizing dimension reduction statistical analysis, wherein the calibration parameter model configures at least an image adjustment process corresponding to the image-context attribute and wherein the image adjustment process is configured to define how to post-process a raw photograph after being captured by the camera module; and cause an image processor to calibrate the raw photograph of the camera module by providing the calibration parameter model to the image processor.
-
Specification