System and method for modulating a peripheral device based on an unscripted feed using computer vision
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Solution Overview
Problem
Current virtual reality systems lack a home-use, stand-alone device capable of delivering target-specific haptics with next-generation realism and zero latency, and do not employ learning-based approaches to enhance user input processing or integrate peripheral devices with audio/video signals for real-time haptic effects.
Innovation Solution
A modular, programmable haptic system that uses computer vision logic to control air flow and temperature for precise haptic delivery, integrating with peripheral devices and learning-based algorithms to predict and react to user inputs, enabling real-time haptic responses and universal integration with various environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a stand-alone home-use haptic device is implemented, then ease of operation and accessibility are improved, but device complexity and integration capabilities deteriorate
Solution Approach 1:
The system is divided into independent modular components including a haptic engine, computer vision processor, and peripheral device interfaces. Each module operates autonomously but can be integrated through standardized protocols, allowing the system to function as a complete stand-alone unit while maintaining the complexity management benefits of modular architecture.
Solution Approach 2:
The haptic engine is designed with universal integration capabilities that allow it to work with multiple types of peripheral devices (audio, video, sensors) through standardized interfaces. This multi-functionality enables the device to serve as a complete home-use system while maintaining compatibility with various external systems, resolving the contradiction between simplicity and integration capability.
2Measurement precision
If learning-based algorithms are implemented for real-time processing, then measurement precision and response accuracy are improved, but use of energy and computational load worsen
Solution Approach 1:
The system pre-trains learning models offline and stores pre-processed patterns in memory. During real-time operation, the system retrieves and applies pre-computed solutions rather than performing full learning computations, thereby maintaining high measurement precision while dramatically reducing real-time energy consumption and computational load.
Solution Approach 2:
The system replaces heavy real-time machine learning computations with optimized lookup tables and simplified decision algorithms that have been pre-computed. This substitution maintains the precision benefits of learning-based approaches while reducing the computational energy requirements to levels suitable for home-use devices.
3Manufacturing precision
If computer vision logic is used for peripheral device modulation, then haptic delivery precision is improved, but device complexity and processing requirements worsen
Solution Approach 1:
The system extracts and isolates the computer vision processing functions into a dedicated subsystem that processes visual input separately from the haptic output generation. This extraction allows the main haptic engine to focus on precise actuation while the vision subsystem handles the complex image processing, thereby maintaining high haptic delivery precision while managing overall system complexity through functional separation.
4Reliability
If zero latency haptic delivery is achieved, then reliability and user experience are improved, but device complexity and control precision requirements worsen
Solution Approach 1:
The haptic engine incorporates built-in predictive algorithms that anticipate user actions and pre-adjust haptic parameters before the actual interaction occurs. This self-service capability allows the system to maintain zero latency performance without requiring extremely complex real-time control systems, as the engine proactively prepares responses based on predicted user needs.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides a highly immersive and realistic haptic experience with reduced latency, allowing for universal integration and real-time processing of user inputs, breaking the limitations of content support hurdles and enabling a fully immersive experience without the need for complex installations.
Implementation Method 1
control an air flow intensity... deliver a haptic output to a user
Implementation Method 2
control a temperature element for heating or cooling the air flow
Implementation Method 3
control a temperature element for heating or cooling the air flow
Data Source
AI summary
A system for processing at least one of an audio or video input for non-scripted modulation of at least one peripheral device, comprising: the at least one peripheral device in physical contact with at least one user or free from the at least one user and in communication with at least a first device playing at least one of an original programming feed or live feed unscripted with modulation triggers; a processor; a memory element coupled to the processor; a program executable by the processor to: recognize at least one of the audio or video input from the at least one of the original programming feed or live feed, and determine for at least one tagged event, at least one of a pixel color score, a pixel velocity score, an event proximity score or an audio score; and convert the at least one scored event into at least one of an output command that triggers or controls a modulation effect of the at least one peripheral device in physical contact or free from the user in communication with the at least the first device playing the at least one of the original programming feed or live feed, thereby enabling modulation of the at least one peripheral device based on any programming comprising at least one of an audio or video input and not requiring scripted modulation triggers.