Complementary Data Generation for VR Avatar Tracking
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Solution Overview
Problem
Current virtual reality systems face challenges in providing immersive experiences due to inadequate motion tracking, particularly in synchronizing player movements with avatar movements, especially for amputees and in generating realistic finger and prosthetic limb movements.
Innovation Solution
A system that uses wearable sensors and a processor to analyze tracking data, generate complementary movement data for missing body parts, and combine it with existing data to create a more immersive and realistic avatar animation, including the use of key pose libraries and inverse kinematics to predict movements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If motion tracking is implemented with limited sensors, then device complexity is reduced, but measurement precision of body part movements deteriorates
Solution Approach 1:
The system introduces complementary movement data as an intermediary element that bridges the gap between limited tracking data and complete avatar animation. This complementary data acts as a mediator that fills in missing information from untracked body parts, allowing the system to maintain measurement precision without requiring additional tracking sensors.
Solution Approach 2:
The system creates copies of movement patterns from tracked body parts and applies them to untracked body parts. By copying and adapting movement data from available sensors to generate complementary animation data for missing body parts, the system maintains realistic avatar representation without requiring direct tracking of every body part.
2Reliability
If complete body tracking is implemented, then immersion is improved, but device complexity increases
Solution Approach 1:
The system implements partial action by tracking only essential body parts rather than attempting to track every body part completely. By focusing tracking resources on key body parts and generating complementary data for the remainder, the system achieves sufficient immersion quality without the complexity of complete body tracking.
Solution Approach 2:
The system enables self-service by using the limited tracking data that is collected to automatically generate complementary movement data for untracked body parts. The system serves itself by deriving additional information from existing sensors through algorithms that infer movements of untracked body parts based on tracked body part movements.
3Measurement precision
If sensors are placed on all body parts, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The system extracts and removes the requirement for sensors on all body parts by identifying that complete body part instrumentation is not necessary. By taking out the unnecessary sensors and relying instead on complementary data generation from a limited sensor set, the system maintains measurement precision while dramatically improving ease of operation.
Data Source
AI summary
A system for generating complementary data for a visual display that includes one or plurality of wearable sensors that collect tracking data for a users position, orientation, and movement. The sensor(s) are in communication with at least one processor that may be configured to receive tracking data, identify missing tracking data, generate complementary data to substitute for missing tracking data, generate a 3D model comprised of tracking data and complementary data, and communicate the 3D model to a display. Complementary tracking data may be generated by comparison to a key pose library, by comparison to past tracking data, or by inverse kinematics.