- Number
- 11158286
- Published
- 2021-10-26
- Filed
- 2019-03-18
- Assignee
- Disney Enterprises, Inc.
- Inventors
- Yaacob; Yazmaliza, Narayan; Nimesh C., Grubin; Kari M., Wahlquist; Andrew J.
- CPC
- G06N3/094; G06N5/025; G06V10/25; G06N3/0475; G09G5/02; G06N5/01; G06N20/00; G06N3/09; G06N3/0464; G09G5/06; H04N1/6063; G06T7/90
- Verdict
- Set aside ML color science conversion, generic image processing
- Source
- Google Patents · FreePatentsOnline
Abstract
Techniques are disclosed for converting image frames from one color space to another while predicting artistic choices that a director, colorist, or others would make. In one configuration, a color conversion application receives image frames, an indication of color spaces to convert between, and metadata associated with the image frames and/or regions therein. The conversion application determines a global, base color conversion for the image frames using a predefined color space transformation. Then, the conversion application (optionally) extracts image regions depicting objects of interest in the image frames, after which the color conversion application processes each of the extracted image regions and the remaining image frames (after the extracted regions have been removed) using one or more functions determined using machine learning. The processed extracted regions and remainders of the image frames are then combined by the color conversion application for output.
Background
BACKGROUND Field of the Disclosure (1) Aspects presented in this disclosure generally relate to color conversion. Description of the Related Art (2) Colors have been used in motion pictures to convey emotions and different elements of a scene. Color conversion is required to adjust image frames to different display environments, such as converting from the theatrical P3 (DCI) color space to the in-home Rec. 709 (BT. 709) color space with a constrained set of colors relative to the P3 color space, or from the Rec2020 color space to the P3 D65 color space. Traditionally, color conversions have required a director, colorist and/or others to manually decide on the brightness, saturation, image adjustments, etc. needed to create a representation of image frames in another color space. Such a manual color conversion process, which is also sometimes referred to as a “trim pass,” can be labor intensive and time consuming. This is particularly the case with the proliferation of new display technologies that support different color spaces, necessitating ever more color conversions. SUMMARY (3) One aspect of this disclosure provides a computer-implemented method for converting image frames from a first color space to a second color space. The method generally includes receiving one or more image frames represented in the first color space, the one or more image frames being associated with corresponding metadata. The method further includes, for each image frame of the one or more image
Claims
1. A computer-implemented method for converting image frames from a first color space to a second color space, the computer-implemented method comprising: receiving one or more image frames represented in the first color space, the one or more image frames being associated with creative metadata specific to the one or more image frames, the creative metadata indicating a genre and a scene type; performing a base color conversion of the one or more image frames into one or more initial converted image frames in the second color space via a color space transformation, wherein the first color space has a different gamut of colors than the second color space; extracting, from the one or more initial converted image frames and using a trained model, object regions depicting one or more objects of interest; adjusting, by operation of one or more computer processors and using a first function of a plurality of functions trained using machine learning, one or more colors of a first object region of the object regions based on the genre; adjusting, using a second function of the plurality of functions, one or more colors of a second object region of the object regions based on the scene type, wherein the second function is distinct from the first function; and combining the object regions and a remainder of the one or more initial converted image frames to generate for output one or more final converted image frames in the second color space. ||
9. A non-transitory computer-readable medium including instructions executable to convert image frames from a first color space to a second color space, by performing operations comprising: receiving one or more image frames represented in the first color space, the one or more image frames being associated with creative metadata specific to the one or more image frames, the creative metadata indicating a genre and a scene type; performing a base color conversion of the one or more image frames into one or more initial converted image frames in the second color space via a color space transformation, wherein the first color space has a different gamut of colors than the second color space; extracting, from the one or more initial converted image frames and using a trained model, object regions depicting one or more objects of interest; adjusting, by one or more computer processors and using a first function of a plurality of functions trained using machine learning, one or more colors of a first object region of the object regions based on the genre; adjusting, using a second function of the plurality of functions, one or more colors of a second object region of the object regions based on the scene type, wherein the second function is distinct from the first function; and combining the object regions and a remainder of the one or more initial converted image frames to generate for output one or more final converted image frames in the second color space. ||
14. A system, comprising: one or more computer processors; and a memory containing a program that, when executed on the one or more computer processors, performs an operation for converting image frames from a first color space to a second color space, the operation comprising: receiving one or more image frames represented in the first color space, the one or more image frames being associated with creative metadata specific to the one or more image frames, the creative metadata indicating a genre and a scene type; performing a base color conversion of the one or more image frames into one or more initial converted image frames in the second color space via a color space transformation, wherein the first color space has a different gamut of colors than the second color space; extracting, from the one or more initial converted image frames and using a trained model, object regions depicting one or more objects of interest; adjusting, using a plurality of functions trained using machine learning, one or more colors of a first object region of the object regions based on the genre; adjusting, using a second function of the plurality of functions, one or more colors of a second object region of the object regions based on the scene type, wherein the second function is distinct from the first function; and combining the object regions and a remainder of the one or more initial converted image frames to generate for output one or more final converted image frames in the second color space.