Data Processing for Environmental Object Detection in Immersive Content
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Solution Overview
Problem
Users interacting with immersive content in a room may accidentally collide with objects, risking injury or damaging them, while existing systems fail to account for the nature of these objects to enhance user safety and experience.
Innovation Solution
A system that recognizes and classifies objects in the user's environment using convolutional neural networks, providing feedback through augmented reality to guide safe interaction by recommending object removal or incorporation based on their characteristics, and allowing user feedback to improve object recognition accuracy over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the user moves around the room to interact with immersive content, then the user experience quality is improved, but the risk of collision with objects causing injury or damage increases
Solution Approach 1:
The system performs preliminary detection and classification of objects in the environment before the user interacts with immersive content. By identifying hazardous objects in advance and providing warnings or automatic restrictions, the system prevents collisions before they occur, thus maintaining safe interaction while allowing user movement.
Solution Approach 2:
The system continuously monitors the environment and provides real-time feedback to the user about detected objects and potential collision risks. This feedback loop allows the user to adjust their movements accordingly, enabling safe interaction with immersive content while maintaining high user experience quality.
2Reliability
If the system detects and classifies objects in the environment, then user safety is improved, but the device complexity increases
Solution Approach 1:
The system replaces complex mechanical safety systems with software-based computer vision and machine learning algorithms. By using neural networks to detect and classify objects, the system achieves high reliability for user safety without requiring complex mechanical sensors or physical barriers.
Solution Approach 2:
The system creates digital representations (copies) of physical objects in the environment through image processing and object detection. These digital models are then classified and analyzed to determine safety risks, allowing the system to assess environmental hazards without direct physical interaction with objects.
3Reliability
If the system provides real-time object detection and feedback, then collision prevention is improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary object detection and classification before the user begins interacting with immersive content. By pre-processing the environmental data and identifying hazardous objects in advance, the system reduces the computational burden during real-time interaction, minimizing processing delays while maintaining collision prevention capability.
Data Source
AI summary
A data processing apparatus includes circuitry configured to: receive an image of a user in an environment; determine a region of the environment in the image in which motion of the user is expected, the motion of the user being associated with interactive content experienced by the user; identify one or more attributes of a detected object in the image, a portion of the detected object being within the determined region of the environment; determine a predetermined process associated with the one or more identified attributes; and perform the predetermined process.