3D Conversations in an Artificial Reality Environment

Smart overview of the Invention

A 3D conversation system enables users to engage in conversations within an augmented reality environment, simulating face-to-face interactions. The system operates through a series of data processing stages, including calibration, capture, tagging, filtering, compression, decompression, reconstruction, rendering, and display. This pipeline captures images from the sending user and transforms them into a viewpoint that aligns with the receiving user, ensuring synchronized audio and visual output.

Technical Field and Background

The technology focuses on enhancing communication methods by facilitating three-dimensional (3D) conversations between multiple devices. Traditional video conferencing lacks the depth of in-person interactions due to its reliance on two-dimensional (2D) displays that hinder understanding of body language and spatial dynamics. The 3D conversation system aims to overcome these limitations by allowing participants to move relative to one another in a more immersive experience.

Pipeline Stages Explained

The pipeline involves several key stages:

• Capture: Collects audio, images, and depth data using various devices.
• Tag and Filter: Enhances data quality and removes unnecessary components.
• Compression/Decompression: Prepares data for transmission and restores it for processing.
• Reconstruction: Creates a 3D representation of the sending user from captured data.
• Render: Generates 2D images from the 3D representation tailored to the receiving user's display.
• Display: Outputs the rendered images while synchronizing with audio.

Calibration Stage

The calibration stage is crucial for ensuring accurate data capture. It gathers intrinsic parameters (fixed camera features) and extrinsic parameters (contextual conditions) that characterize how light is interpreted by the camera. Each camera involved in the conversation can be calibrated individually, allowing for precise mapping between camera coordinates and pixel coordinates in images.

Dynamic Adaptation Based on Context

The system is designed to adapt dynamically based on conversation context, which includes factors like processing capacity, bandwidth availability, and user settings. This flexibility allows for optimized performance during conversations by utilizing appropriate resources and configurations based on real-time conditions, enhancing the overall user experience in augmented reality interactions.