CROWD REMOVAL AND AUTOMATIC FOCUS FOR IMAGES

Number: 20250259309
Published: 2025-08-14
Filed: 2024-02-09
Assignee: DISNEY ENTERPRISES, INC.
Inventors: Iglesias Navarro; Santiago et al.
CPC: G06T7/11
Verdict: Set aside image editing, generic/business
Source: Google Patents · FreePatentsOnline

Abstract

A computer implemented method includes receiving, by a processor, an image including one or more subjects and one more obstructions. The method further includes partitioning, by the processor, the image into a plurality of image segments, where the one or more subjects and one or more obstructions are represented as separate image segments of the plurality of image segments. The method further includes obtaining, by the processor, depth information for the plurality of image segments. The method further includes identifying one or more focal image segments of the plurality of image segments based on the depth information of the plurality of image segments and modifying the image based on the one or more focal image segments to generate a modified image.

Background

BACKGROUND

Often, people may capture images at a variety of densely packed locations, such as tourist attractions and theme parks. Such images may include the subjects of interest (e.g., a family) but also include many other people and objects that also are in the area at the time of the image capture. As such, it may be desirable to remove or replace unwanted people (e.g., crowd or strangers) or objects from the image. More specifically, certain environments that are commonly suitable for photography (such as amusement parks or other tourist attractions), the high volume of guests may make it difficult to take a portrait photo without any unwanted people or obstructions in the background. Thus, it may desirable after a photo is taken to determine the focal subject(s) of the image and remove any unwanted obstructions from the image. Additionally, obstruction removal may provide better user experience for commercial portrait photography by streamlining the editing process and providing for consistent image backgrounds.

Current methods for removing unwanted obstructions in images are manual and require a user to manually designate objects in the image that are undesirable and select the objects for removal. These methods are time-consuming and impractical where there are many obstructions in an image. For example, for an image with a large crowd of people obstructing the background, manual methods may require selection and removal of each person in the crowd. Furt

Claims

1. A computer implemented method comprising: receiving, by a processor, an image including one or more subjects and one or more obstructions; partitioning, by the processor, the image into a plurality of image segments, wherein the one or more subjects and one or more obstructions are represented as separate image segments of the plurality of image segments; obtaining, by the processor, depth information for the plurality of image segments; identifying one or more focal image segments of the plurality of image segments based on the depth information of the plurality of image segments; and modifying the image based on the one or more focal image segments to generate a modified image. || 15. An image editing system for automatic detection and editing of image obstructions, comprising: an image data storage comprising a plurality of images; and a processor configured to modify the plurality of images, wherein the processor is configured to: receive an image including one or more subjects and one or more obstructions; partition the image into a plurality of image segments, wherein the one or more subjects and one or more obstructions are represented as separate image segments of the plurality of image segments; obtain depth information for the plurality of image segments; identify one or more focal image segments of the plurality of image segments based on the depth information of the plurality of image segments; and modify the image based on the one or more focal image segments to generate a modified image. || 23. The system or claim 18, wherein assigning a focal cluster of segments based on the depth and position of segments relative to the focal point segment comprises assigning an initial focal cluster of segments, wherein the initial focal cluster of segments includes the focal point segment and other segments that are within a threshold depth and distance from the focal point segment and have an average depth and position score above a threshold average depth and position score.