Dynamic Haptic Generation from Video Event Detection
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Solution Overview
Problem
Existing haptic effect generation in devices often occurs late in the development process, resulting in inadequate association of haptic effects with audio or video events, and lacks customization for specific events.
Innovation Solution
A method and system that dynamically generate haptic effects by detecting video events, collecting related data, configuring feature parameters, and automatically producing tailored haptic effects based on the type of event, such as collisions or explosions, using video and audio data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If haptic effects are added late in the development process, then development time is reduced, but the association quality between haptic effects and audio/video events deteriorates
Solution Approach 1:
The system performs preliminary action by automatically generating haptic effect parameters early in the development process through video event detection and analysis. The video processing system extracts event information (collisions, explosions, etc.) and automatically configures haptic parameters without waiting for late-stage manual integration, thus maintaining both time efficiency and association quality.
Solution Approach 2:
The system implements self-service by using the video content itself to automatically generate haptic effect parameters. The video processing system detects events within the video data and uses that information to configure haptic parameters without requiring external manual input from developers, enabling autonomous haptic integration that preserves both development speed and precision.
2Adaptability or versatility
If manual selection of haptic effects is used, then customization for specific events is improved, but development complexity increases
Solution Approach 1:
The system replaces the manual mechanical process of haptic effect selection with an automated computational system. The video processing system automatically detects video events, extracts relevant features, and generates haptic parameters through algorithmic processing, eliminating the need for manual developer intervention while maintaining event-specific customization.
Solution Approach 2:
The system achieves customization through dynamic parameter changes based on detected video events. By automatically analyzing video content and adjusting haptic parameters (intensity, duration, frequency) according to the specific event type detected, the system provides event-specific customization without requiring manual configuration for each scenario.
3Productivity
If automated haptic generation is implemented, then development time is reduced, but haptic effect quality may deteriorate
Solution Approach 1:
The system incorporates feedback by using video event detection results to inform and adjust haptic parameter generation. The automated process continuously monitors video content, detects events, and uses that information to configure appropriate haptic parameters, ensuring that automation maintains quality through data-driven decision-making rather than generic defaults.
Solution Approach 2:
The system performs preliminary analysis of video content to prepare accurate haptic parameters before actual haptic output is needed. By pre-processing video data to extract event information and configure parameters in advance, the system ensures that automated generation produces high-quality results ready for immediate implementation without compromising effectiveness.
Data Source
AI summary
A method or system that receives input media including at least video data in which a video event within the video data is detected. Related data that is associated with the detected video event is collected and one or more feature parameters are configured based on the collected related data. The type of video event is determining and a set of feature parameters is selected based on the type of video event. A haptic effect is then automatically generated based on the selected set of feature parameters.