Event-Based Eye Blink Detection for Low-Light Precision
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Solution Overview
Problem
Conventional cameras struggle to accurately detect eye blink patterns due to the small size of the eye and brief duration of blinks, especially in low-light conditions, and high-speed cameras increase costs and data processing demands.
Innovation Solution
An eye blink detection method using a DVS camera that integrates asynchronous DVS pixels to form frames, identifying patterns of color regions in the eye region to determine eye blink actions, frequency, and duration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional cameras with 30 frames per second are used, then the device complexity and cost are low, but the measurement precision of eye blink duration and the clarity of eye blink images deteriorate
Solution Approach 1:
The patent changes the temporal sampling parameter from 30 fps to asynchronous event-based sampling with millisecond resolution. This parameter change enables precise capture of fast eye blink events (lasting only a fraction of a second) without requiring expensive high-speed cameras, thus resolving the contradiction between device complexity and measurement precision.
2Measurement precision
If high-speed cameras with frame rates in excess of 100 frames per second are used, then the measurement precision of eye blink detection is improved, but the device complexity and data processing requirements increase significantly
Solution Approach 1:
The patent replaces the mechanical frame-based capture system with an asynchronous event-based system. Instead of capturing complete frames at fixed intervals, the system only captures pixel-level events when light intensity changes occur, substituting the mechanical scanning and frame buffering processes with a more efficient event-driven architecture that reduces device complexity while maintaining high measurement precision.
3Device complexity
If conventional cameras are used, then the device complexity is low, but the measurement precision of eye blink frequency and the accuracy in low-light conditions deteriorate
Solution Approach 1:
The patent segments the image into multiple pixels, each independently detecting light intensity changes. This segmentation allows the system to capture eye blink events at pixel level with millisecond precision, improving frequency measurement accuracy without requiring a complex high-speed camera system. The asynchronous event stream from segmented pixels can be processed to reconstruct eye blink patterns accurately.
Data Source
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AI summary
An eye blink detection method and system are disclosed. The eye blink detection method comprises: photographing a face using a DVS camera to obtain a stream of DVS pixels; integrating DVS pixels of the stream of DVS pixels to form a plurality of DVS frames, wherein each of the plurality of DVS frames comprises a plurality of first color pixels and a plurality of second color pixels, each of the first color pixel being associated with one or more DVS pixels indicating a brightening event and each of the second color pixel being associated with one or more DVS pixels indicating a darkening event; and determining whether there exists an eye blink action in at least one DVS frame of the plurality of DVS frames, wherein the step of determining whether there exists an eye blink action comprises: determining whether there exists a pattern in which a first color region and a second color region are distributed one above the other in an eye region of the at least one DVS frame.