Biometric Video Augmentation for Immersive HMD Experience
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Solution Overview
Problem
Raw image or audio data captured by head-mounted displays (HMDs) may not adequately convey the full range of emotions or sensations experienced by the user, limiting the immersive experience when shared with others.
Innovation Solution
An image processing system that applies editing techniques such as slow motion, blur, and music synchronization based on biometric data like heart rate, respiration, and movement, to enhance the captured video and audio, potentially in real-time or post-capture, using sensors integrated into the HMD or external devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If raw image or audio data is captured by HMDs, then the device complexity is reduced and ease of operation is improved, but the immersive experience quality deteriorates because it does not adequately convey the full range of emotions or sensations
Solution Approach 1:
The system segments the emotional and sensory information into distinct biometric components (heart rate, respiration rate, sweat production, movement) that can be independently measured and processed. Each biometric parameter is captured by separate sensors and then integrated to create a comprehensive emotional profile, allowing the system to convey nuanced user experiences without requiring a single complex sensor array
Solution Approach 2:
Biometric data serves as an intermediary that bridges the gap between the user's internal emotional state and the external video content. The system uses biometric measurements as intermediate representations of emotions and sensations, which then guide the application of image processing effects to the video data, thereby conveying the user's internal state without directly transmitting neural or emotional signals
2Reliability
If image processing is applied to enhance the viewing experience, then the immersive experience quality is improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary classification of biometric data into discrete emotional and sensory states (e.g., identifying when the user is excited, scared, or experiencing physical exertion). Based on this preliminary classification, pre-defined image processing pipelines are selected and applied, avoiding the need for real-time complex analysis and allowing for faster processing of video data
Solution Approach 2:
The system applies specific parameter changes to video data based on biometric states: adjusting playback speed (time parameter) when the user experiences high arousal states, modifying motion blur parameters when the user is moving rapidly, or adjusting color saturation when the user exhibits strong emotional responses. These targeted parameter adjustments provide meaningful enhancement with minimal computational overhead compared to comprehensive real-time video processing
Data Source
AI summary
Embodiments described herein may allow for dynamic image processing based on biometric data. An example device may include: an interface configured to receive video data that is generated by an image capture device; an interface configured to receive biometric data of a user of the image capture device from one or more sensors generated synchronously with the video data; and an image processing system configured to apply image processing to the video data to generate edited video data. The image processing may be based, at least in part, on the biometric data.