Augmented Reality Object Collision Detection With Depth Buffers
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Solution Overview
Problem
Conventional augmented reality applications require complex image processing techniques for precise object interaction simulations, which are resource-intensive and not necessary for applications like e-commerce and video games, necessitating a more efficient approach.
Innovation Solution
A system and method for detecting object collisions in augmented reality images using simplified collision detection algorithms that reduce computational resources while maintaining a realistic user experience, incorporating real-time collision detection and haptic feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex image processing techniques are used for precise object interaction simulations, then measurement precision and reliability are improved, but use of energy and device complexity increase
Solution Approach 1:
The collision detection process is segmented into distinct phases: depth buffer generation, depth comparison, and collision determination. The detection space is divided into discrete depth buffers that can be independently processed, allowing the system to achieve precise collision detection through modular, efficient processing steps rather than complex continuous analysis.
Solution Approach 2:
The system creates a depth buffer copy representing the virtual object's spatial occupancy and compares it against the environment depth buffer. This copying approach allows precise collision detection by comparing simplified depth representations rather than performing complex geometric intersection calculations, significantly reducing computational resources while maintaining accuracy.
2Measurement precision
If complex image processing techniques are used for precise object interaction simulations, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system replaces complex mechanical-style geometric collision detection algorithms with an optical-inspired depth buffer comparison approach. By using depth maps and pixel-level depth comparison (similar to how human vision perceives depth), the system achieves precise collision detection with simpler processing logic, reducing device complexity while maintaining high measurement precision.
Solution Approach 2:
The depth buffer serves as an intermediary data structure that mediates between the virtual object geometry and the collision detection logic. Instead of directly comparing complex 3D geometries, the system uses the depth buffer as an intermediate representation that simplifies the comparison process, reducing system complexity while preserving detection precision.
3Use of energy by moving object
If simplified collision detection algorithms are used, then use of energy and device complexity are reduced, but measurement precision deteriorates
Solution Approach 1:
The system changes the parameter representation from complex geometric models to simplified depth buffer values at each pixel location. By transforming the collision detection problem into a parameter comparison task (comparing depth values rather than geometric shapes), the system achieves both energy efficiency and high precision. The depth buffer parameters capture essential spatial information while enabling simple, fast comparisons.
Solution Approach 2:
The system transitions from 3D geometric collision detection to 2D depth buffer comparison. By projecting the 3D collision problem onto a 2D depth buffer plane and performing pixel-level comparisons, the system simplifies the computational dimensionality while preserving collision detection accuracy. This dimensional transformation enables energy-efficient processing without sacrificing measurement precision.
Data Source
AI summary
A method can include capturing, in real-time via a camera, an image of a real environment. The method further can include determining, using the image, a primary plane in the real environment. The method additionally can include rendering, in real-time on a display device for a user, a virtual object in the image of the real environment. The method also can include detecting a collision by the virtual object in the image, comprising: (a) projecting the virtual object onto the primary plane as a 2D resting plane for the virtual object; (b) determining tracking rays for the virtual object, wherein the tracking rays connect vertices of the 2D resting plane to a viewpoint from the camera; and (c) determining the collision based on whether the tracking rays intersect with a plane of one or more existing physical objects in the image. The method further can include upon determining that the collision is detected, outputting a haptic effect indicating the collision. Other embodiments are disclosed.