Event-Based Vision Sensor Motion Analysis
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Solution Overview
Problem
Motion-based user interfacing schemes using frame-based vision sensors are prone to inaccuracies due to distance variations and incur high manufacturing costs, with frame-based vision sensors having relatively low reaction velocities.
Innovation Solution
A method and apparatus that utilize an event-based vision sensor to generate event signals in response to changes in light from an object, synchronized with a frame-based vision sensor to capture depth information, allowing for accurate motion analysis by compensating for latency and disparity calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frame-based vision sensors are used to recognize motion, then depth information can be obtained, but the reaction velocity is relatively low and manufacturing costs increase
Solution Approach 1:
The system divides the vision function into two separate sensors: an event-based vision sensor for high-speed motion detection and a frame-based vision sensor for depth information and still image capture. Each sensor performs its specialized function, avoiding the need for a single sensor to handle all requirements simultaneously.
Solution Approach 2:
The patent combines event-based vision sensor and frame-based vision sensor into a unified motion analysis system. The event-based sensor provides high-speed motion signals while the frame-based sensor provides depth context, and their data are fused to achieve both high reaction velocity and accurate motion recognition.
2Measurement precision
If frame-based vision sensors are used to recognize motion, then depth information can be obtained, but manufacturing costs increase
Solution Approach 1:
The system divides the vision function into two separate sensors: an event-based vision sensor for high-speed motion detection and a frame-based vision sensor for depth information and still image capture. Each sensor performs its specialized function, avoiding the need for a single sensor to handle all requirements simultaneously.
Solution Approach 2:
The event-based vision sensor serves multiple functions: motion detection, depth estimation through optical flow, and triggering frame-based sensor captures. This multi-functionality reduces the need for additional specialized components, potentially lowering overall system cost.
3Speed
If event-based vision sensor is used, then reaction velocity is high, but depth information acquisition is limited
Solution Approach 1:
The frame-based vision sensor acts as an intermediary that provides depth information and still image context. The event-based sensor triggers frame-based sensor captures at specific moments, and the frame-based sensor's depth data is used to interpret and contextualize the high-speed motion events detected by the event-based sensor.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy and reduces costs by leveraging the high reaction velocity of event-based sensors and the high-resolution data of frame-based sensors, improving motion analysis and depth information extraction.
Implementation Method 1
a first vision sensor configured to generate at least one event signal by sensing at least a portion of an object in which a motion occurs
Implementation Method 2
a second vision sensor configured to generate a current frame by time-synchronously capturing the object
Data Source
AI summary
A method and apparatus for analyzing a motion based on depth information are provided. The method includes: receiving event signals from a first vision sensor configured to generate at least one event signal by sensing at least a portion of an object in which a motion occurs; receiving a current frame from a second vision sensor configured to time-synchronously capture the object; synchronizing the received event signals and the received current frame; and obtaining depth information of the object based on the synchronized event signals and current frame.