Automated Haptic Generation Through Audio-Video Context Analysis
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Solution Overview
Problem
Existing haptic technologies often generate haptic effects that are not contextually accurate for media content, leading to a poor user experience, such as overwhelming haptic responses or mismatched effects during streaming of media content.
Innovation Solution
The implementation of techniques for generating and distributing haptic data based on machine learning (ML) analysis of audio and video content, allowing for real-time generation and adjustment of haptic effects to match the context of the media being streamed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If haptic effects are generated by converting audio signal attributes to haptic signal attributes, then haptic effects can be produced from audio content, but the generated haptic effects may not be contextually accurate and can overwhelm the user
Solution Approach 1:
The patent introduces an intermediary system that receives both audio and video content, analyzes them together to determine contextual information, and then generates haptic effects based on this combined analysis. This intermediary processing layer ensures that haptic effects are contextually accurate by considering both audio and video contexts, rather than simply converting audio attributes directly to haptic attributes.
2Device complexity
If haptic effects are generated based on audio content alone, then the system complexity is reduced, but the haptic effects do not match the visual context of the media content
Solution Approach 1:
The patent merges audio content analysis with video content analysis to generate haptic effects. The system processes both audio and video streams simultaneously, combines the contextual information from both sources, and uses this integrated analysis to produce haptic effects that are synchronized with both the auditory and visual elements of the media content.
3Speed
If haptic effects are generated in real-time during media streaming, then user immersion is enhanced, but the haptic effects may not be precisely tuned to the specific scene context
Solution Approach 1:
The patent performs preliminary analysis of both audio and video content to identify upcoming events, scenes, or contextual elements before they occur in the media stream. This advance analysis allows the system to prepare appropriate haptic effects in advance, ensuring that when the actual event occurs in real-time, the pre-prepared haptic effect can be immediately applied with high contextual precision without compromising real-time performance.
Data Source
AI summary
Embodiments provide systems and techniques for automated generation of haptic effects based on haptics data. An example technique includes obtaining a set of haptic data associated with media content being streamed to a computing device. The media content is displayed on the first computing device. One or more haptic effects are generated using one or more haptic devices while displaying the media content, based on the set of haptic data. One or more parameters of the one or more haptic effects is adjusted when a predetermined condition(s) is satisfied.