Automatic Haptic Effect Tuning via Audio-Driven Filtering
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Solution Overview
Problem
The quality of haptic effects in multimedia content is often degraded due to their late integration in the development process, resulting in inadequate association with audio effects and a lack of human artistic touch in automatic generation algorithms.
Innovation Solution
A system that automatically generates haptic effects from input media such as audio, video, or sensory data and applies filters to tune these effects, incorporating user preferences, localization, and device parameters, using techniques like 'emphasize bumps', 'scenes blending', and 'proximity to action' filters to enhance the quality of haptic feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If haptic effects are added late in the game development process, then the development timeline is maintained, but the quality of haptic effects deteriorates due to inadequate association with audio effects and lack of human artistic touch
Solution Approach 1:
The system performs preliminary action by automatically generating haptic effects during the audio development phase rather than adding them later. The automatic haptic generation algorithm processes audio effects as they are created, establishing the haptic track concurrently with audio development rather than as a separate late-stage process.
Solution Approach 2:
The system applies self-service by using the audio effect data itself to generate the corresponding haptic effects automatically. The same audio effect that drives the audio output also serves as the input for generating the haptic effect track, eliminating the need for separate manual haptic programming and ensuring consistent association between audio and haptic effects.
2Productivity
If automatic haptic generation algorithms are used without human artistic touch, then productivity increases, but the quality and contextual relevance of haptic effects deteriorates
Solution Approach 1:
The system implements feedback by applying multiple filtering stages to the automatically generated haptic effects. The generated haptic track undergoes sequential filtering including low-pass filtering to remove high-frequency noise, de-emphasis filtering to adjust frequency response, and saturation filtering to prevent excessive amplitude values, with each filter stage refining the output based on the previous stage's results.
Solution Approach 2:
The system applies parameter changes by dynamically adjusting filter parameters based on the characteristics of the audio content and desired haptic output. The low-pass filter cutoff frequency, de-emphasis filter coefficients, and saturation threshold values are modified to optimize the haptic effect quality for different types of audio effects and gameplay contexts.
Data Source
AI summary
A system that generates haptic effects receives input media that includes audio data, video data, or sensory data. The system automatically generates a haptic effect track from the input media. The system then applies at least one filter to the automatically generated haptic effect track to generate a tuned haptic effect track.