View-Dependent Virtual Reality Content from RGB-D Images

Abstract

High-fidelity virtual content is essential for the creation of compelling and effective virtual reality (VR) experiences. However, creating photorealistic content is not easy, and handcrafting detailed 3D models can be time and labor intensive. Structured camera arrays, such as light-stages, can scan and reconstruct high-fidelity virtual models, but the expense makes this technology impractical for most users. In this paper, we present a complete end-to-end pipeline for the capture, processing, and rendering of view-dependent 3D models in virtual reality from a single consumer-grade depth camera. The geometry model and the camera trajectories are automatically reconstructed and optimized from a RGB-D image sequence captured offline. Based on the head-mounted display (HMD) position, the three closest images are selected for real-time rendering and fused together to smooth the transition between viewpoints. The specular reflections and light-burst effects can also be preserved and reproduced. We confirmed that our method does not require technical background knowledge by testing our system with data captured by non-expert operators.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2017
Accession Number
AD1160120

Entities

People

  • Chih-fan Chen
  • Evan S. Rosenberg
  • Mark Bolas

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Applied Computer Science
  • Augmented Reality
  • Blending
  • Cameras
  • Computer Graphics
  • Consumers
  • Geometry
  • Graphics
  • Human Supervisory Control
  • Human Systems Integration
  • Image Processing
  • Mixed Reality
  • New York
  • Optimization
  • Pipelines
  • Ray Tracing
  • Reflection
  • Sequences
  • Specular Reflection
  • Transitions
  • Virtual Reality

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Human-Computer Interaction (HCI).
  • Neural Network Machine Learning.