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Interesting Patents | Electronic Arts – Revolutionizing the Gaming Industry with AI-Driven 3D Reconstruction of Real-World Objects

Interesting Patents - Electronic Arts - Revolutionizing the Gaming Industry with AI-Driven 3D Reconstruction of Real-World Objects

Interesting Patents | Electronic arts | Tuesday, april 4, 2023

The United States Patent and Trademark Office (USPTO) grants hundreds of new patents every week, showcasing developments in technology and innovation. In our Interesting Patents series, we highlight exciting US patent applications and patents recently issued by the USPTO. The patent system enables the protection of innovative ideas, and newly published patent applications provide a glimpse into the future of technology and innovation.

In this edition of #InterestingPatents, we look at Electronic Arts Inc.’s (EA) new patent: Three Dimensional Reconstruction Of Objects Based On Geolocation And Image Data.

EA’s latest patent signals a major advancement in the gaming industry, as it introduces a novel method of generating realistic three-dimensional (3D) representations of real-world objects using artificial intelligence (AI) and machine learning technologies. This breakthrough approach utilizes geolocation and image data to create detailed 3D reconstructions, significantly streamlining the process and overcoming the limitations of traditional 3D scanning techniques. In this article, we delve into the specifics of EA’s patent and discuss its potential impact on the gaming industry, paving the way for more immersive and life-like virtual experiences.

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Three Dimensional Reconstruction Of Objects Based On Geolocation And Image Data

ASSIGNEE: Electronic Arts Inc.
US PAT. NO. 11,620,800 B2

INVENTION OVERVIEW:

The video game industry has long been on the cutting edge of creating immersive experiences that blur the lines between the virtual and the real world. Game developers and artists have used various techniques to recreate three-dimensional (3D) representations of real-world objects and environments. However, traditional methods of 3D scanning can be time-consuming, labor-intensive, and poorly suited for large-scale projects. Now, a EA’s patent seeks to address these challenges by leveraging artificial intelligence (AI) and machine learning technologies to streamline and improve the process of creating realistic 3D content for video games.

Traditionally, game developers have relied on manual 3D scanning techniques to create digital representations of real-world objects in their virtual environments. This process often involves scanning individual objects using specialized equipment, which can be time-consuming and impractical for large-scale applications. Scanning studios may also need help accommodating massive objects like buildings or mountains, further limiting the scope of these techniques.

EA’s patent discloses a method using AI and machine learning to generate detailed 3D representations of real-world objects based on images and geolocation data. By employing a machine learning model, the method can identify and determine the depth of objects in an input image, obtain 3D object data, and generate a virtual 3D representation.

Moreover, the method modifies the 3D representation based on the characteristics of the depicted objects in the image, such as height, width, length, or shape. This modified 3D representation is then arranged in a virtual space, rendering a two-dimensional view of the scene. The system compares this view to the original image to ensure accuracy and stores the final 3D representation with geolocation data.

  1. Efficient object identification: The machine learning model can efficiently segment an input image, identify objects, and determine their depth, streamlining the process of creating 3D representations.
  2. Enhanced accuracy: By modifying the 3D representation based on object characteristics and comparing the rendered view to the original image, the method ensures high accuracy in the final 3D representation.
  3. Scalability: This AI-driven method overcomes the limitations of traditional 3D scanning techniques, enabling large-scale applications and the incorporation of large, macro-sized objects.
  4. Real-world integration: The method’s reliance on geolocation data allows for seamless integration of 3D representations into virtual environments, further enhancing the gaming experience.

EA’s patent represents a significant leap forward in video game development, promising to revolutionize the industry with its AI-driven 3D reconstruction of real-world objects. By overcoming the limitations of traditional 3D scanning techniques, this innovative method can pave the way for more immersive and realistic virtual experiences for gamers everywhere. As AI and machine learning continue to advance, we can expect even more groundbreaking applications to emerge soon.

Interesting Patents EA Revolutionizing the Gaming Industry with AI-Driven 3D Reconstruction of Real-World Objects
Interesting Patents EA Revolutionizing the Gaming Industry with AI-Driven 3D Reconstruction of Real-World Objects
Interesting Patents EA Revolutionizing the Gaming Industry with AI-Driven 3D Reconstruction of Real-World Objects
Interesting Patents EA Revolutionizing the Gaming Industry with AI-Driven 3D Reconstruction of Real-World Objects
Interesting Patents EA Revolutionizing the Gaming Industry with AI-Driven 3D Reconstruction of Real-World Objects

PATENT ABSTRACT:

Embodiments of the systems and methods described herein provide a three dimensional reconstruction system that can receive an image from a camera, and then utilize machine learning algorithms to identify objects in the image. The three dimensional reconstruction system can identify a geolocation of a user, identify features of the surrounding area, such as structures or geographic features, and reconstruct the scene including the identified features. The three dimensional reconstruction system can generate three dimensional object data for the features and/or objects, modify the three dimensional objects, arrange the objects in a scene, and render a two dimensional view of the scene.

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