Search

KR-20260066330-A - Shooting simulation system and method using the same

KR20260066330AKR 20260066330 AKR20260066330 AKR 20260066330AKR-20260066330-A

Abstract

One embodiment of the present invention provides a shooting simulation system for simulating the shooting style of a specific photographer or director, comprising: a setting information collection module that receives setting information of the video equipment regarding a shooting image through a setting information unit provided in the video equipment of a professional photographer, and collects setting information corresponding to an individual shooting image by storing it as a meta value; an artificial intelligence model that performs machine learning using a data set containing the shooting image and setting information provided from the setting information collection module as learning information, is designed to provide setting information of the video equipment that captured the image as output information by analyzing an image input by a user, and performs machine learning optimized for a specific user using the data set containing the image and setting information as learning information; and a setting information extraction module that inputs a sample image selected or input by a user into the artificial intelligence model, extracts standard setting information for the sample image in a preset manner, and then provides the standard setting information to the user.

Inventors

  • 김미연

Assignees

  • 김미연

Dates

Publication Date
20260512
Application Date
20241104

Claims (9)

  1. As a shooting simulation system for simulating the shooting style of a specific writer or director, A setting information collection module that receives setting information of the video equipment regarding a captured image through a setting information unit equipped in the video equipment of a professional photographer, and collects setting information corresponding to an individual captured image by storing it as a metadata value; An artificial intelligence model that performs machine learning using a dataset including captured images and setting information provided from the above setting information collection module as learning information, is designed to provide setting information of the video equipment that captured the image as output information by analyzing an image input by a user, and performs machine learning optimized for a specific user using the dataset including the image and setting information as learning information; and A setting information extraction module comprising: inputting a sample image selected or entered by a user into the artificial intelligence model to extract standard setting information for the sample image in a preset manner, and then providing the standard setting information to the user. Photographic simulation system.
  2. In claim 1, The above-mentioned configuration information collected through the above-mentioned configuration information collection module is, The above-mentioned imaging equipment includes at least one of lighting information, color tone information, contrast information, focal length information, and filter value information, and The above artificial intelligence model is, Designed to learn patterns of setting information characterizing the shooting style of professional photographers based on the above dataset, Photographic simulation system.
  3. In claim 1, It further includes a subject analysis module that analyzes the composition of the subject constituting a sample image taken by a professional photographer in a preset manner and provides subject imitation information to the user; The above subject analysis module is, Configured to display at least one subject information constituting the above sample image on a user's video equipment in a preset manner, Photographic simulation system.
  4. In claim 3, The above subject analysis module is, The composition of the subject constituting the above sample image is divided into a main subject and a sub-sub The degree of matching between the captured image and the sample image captured by the above video equipment is evaluated in a preset manner and provided to the user, wherein the weights for the main subject and the sub-subject are different. When there are multiple sub-subjects, configured to allow the user to select whether to apply individual sub-subjects during the matching degree calculation. Photographic simulation system.
  5. In claim 4, The above subject analysis module is, The shadows of the subject composition constituting the above sample image are analyzed in a preset manner to calculate light source information, and The matching degree is configured to be calculated by further considering the consistency of the light source information of the above-mentioned captured image and sample image, The light source information includes at least one of the position of the light source relative to the subject, the direction of light irradiated from the light source, and the relative intensity of the light source. Photographic simulation system.
  6. A method using a photographic simulation system according to any one of claims 1 to 5, (a1) A step in which setting information of the video equipment for a captured image is transmitted to a setting information collection module through a setting information unit provided in the video equipment of a professional photographer, and setting information corresponding to an individual captured image is stored and collected as a meta value; (a2) A step in which machine learning is performed in an artificial intelligence model using a dataset including captured images and setting information provided by the setting information collection module as learning information; (a3) A step of extracting reference setting information of a sample image selected by a user or input through the above artificial intelligence model in a preset manner; (a4) A step in which the reference setting information extracted in step (a3) is provided to the user through a setting information extraction module so that the user's video equipment is controlled; comprising, method.
  7. In claim 6, After the above (a3) step, (a5) a step in which the subject composition constituting the sample image of step (a3) is analyzed through a subject analysis module to generate subject information, wherein the subject information is configured to be displayed in a manner pre-set on the user's video equipment; further comprising method.
  8. In claim 7, After the above (a5) step, (a6) A step of classifying the subject composition into a main subject and a sub-sub method.
  9. In claim 6, In the above (a4) step, The change setting information, which changes the position of the light source or the position or number of cameras differently from the reference setting information extracted in step (a3), is provided to the user so that the user's video equipment is controlled. method.

Description

Shooting simulation system and method using the same The present invention relates to a shooting simulation system and a method using the same. With the widespread adoption of digital photography and videography, there has been a significant increase in demand to emulate the shooting styles of specific photographers or video directors. In particular, there are many attempts to reproduce specific shooting styles to maximize artistic effects or maintain a consistent brand image. These styles include tone, lighting, focal length, contrast, and specific color filters, and their combinations can be recognized as the unique shooting style of a particular artist or director. Traditionally, to replicate this style, the cinematographer had to analyze the shooting techniques of the author or director and manually set the lighting, exposure, and camera settings. However, since this method relies heavily on the cinematographer's experience and technical skill level, it is difficult for non-professional general users to accurately reproduce the same style. Furthermore, maintaining the same style while shooting amidst varying weather conditions, lighting factors, and subject movement becomes an even more challenging task. With the recent rapid advancement of machine learning technology, research is underway to automatically predict specific shooting styles by collecting and training various shooting data. By analyzing image metadata (e.g., focal length, aperture value, shutter speed, etc.) through machine learning, it is possible to estimate the shooting style based on this and automatically generate shooting settings that mimic a specific style. However, conventional technologies primarily focus on simple image correction, so they have limitations in directly recommending or providing the shooting settings required for the original style. Furthermore, a system that provides real-time setting values based on the captured image, allowing users to refer to those settings when shooting, has not yet been developed. Consequently, photographers must still manually adjust individual settings to replicate styles, which presents problems such as being time-consuming and costly, and making it difficult to guarantee consistency in the final results. Related prior art is disclosed in Japanese Patent Publication No. 2023-013061, "Information processing device, information processing method and program." The prior art discloses a technology that provides a user with a "shooting recipe" composed of shooting setting items, and provides a shooting recipe corresponding to said keyword based on the user's keyword search. When the user inputs keywords such as a person, place, or specific object, the technology provides the user with shooting setting values corresponding to the shooting recipe to perform control, such as calibrating the user device. However, the above-mentioned prior art has limitations in that it merely provides a shooting recipe to the user and does not disclose specific details for imitating the works of famous writers or directors. (Patent Document 1) Japanese Published Patent No. 2023-013061 Other aspects, features, and benefits of specific preferred embodiments of the present invention, as described above, will become more apparent from the following description in conjunction with the accompanying drawings. FIG. 1 is a conceptual diagram of a shooting simulation system according to one embodiment of the present invention. FIG. 2 is a block diagram showing the configuration of a shooting simulation system according to one embodiment of the present invention. FIG. 3 schematically illustrates the process of outputting setting information of an image device through an artificial intelligence model on which machine learning is performed in a shooting simulation system according to one embodiment of the present invention. FIG. 4 is a schematic diagram showing the process of calculating the matching degree through the subject analysis module of a shooting simulation system according to one embodiment of the present invention. FIG. 5 is a flowchart of a method using a shooting simulation system according to one embodiment of the present invention. Hereinafter, various embodiments of the present invention are described with reference to the accompanying drawings. The present invention is not limited to specific embodiments and should be understood to include various modifications, equivalents, and/or alternatives of the embodiments of the present invention. In connection with the description of the drawings, similar reference numerals may be used for similar components. In this document, expressions such as "have," "can have," "include," or "can include" refer to the existence of the relevant feature (e.g., numerical, functional, behavioral, or component, etc.) and do not exclude the existence of additional features. In the present invention, expressions such as “A or B,” “at least one of A or/and B,” or “one or more of A or/a