3D Scanner Using Event-Based Vision for Moving Object Reconstruction
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Solution Overview
Problem
Traditional three-dimensional scanning techniques are inadequate for capturing moving objects due to their reliance on frame-based cameras, which result in artifacts from subtle movements and high computational demands, and conventional systems using event detection sensors require blinking markers for reconstruction, limiting their applicability and accuracy.
Innovation Solution
A three-dimensional scanner system utilizing dynamic vision sensors (DVS) that detects light intensity changes as events, supplemented with additional information about colors, shape, and movements to reconstruct moving objects without the need for markers, allowing for accurate reconstruction from diverse angles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frame-based cameras are used for three-dimensional scanning, then image capture capability is provided, but motion artifacts occur and computational complexity increases
Solution Approach 1:
The patent extracts only the essential information needed for 3D reconstruction by using event-based sensors that detect and transmit only pixels with intensity changes above a threshold. This removes redundant data transmission and processing, directly reducing computational complexity while maintaining reconstruction accuracy for moving objects.
Solution Approach 2:
The system transitions from static frame-based capture to dynamic event-based capture, where sensors continuously monitor and respond to changes in the scene. This dynamic approach allows the system to adapt to moving objects in real-time, reducing motion artifacts without requiring complex synchronization of multiple cameras.
2Speed
If event detection sensors are used for high temporal resolution, then motion capture capability improves, but marker dependency increases
Solution Approach 1:
The system enables objects to be scanned without external markers by using the object's own visual features and the event-based sensor's ability to detect changes. The sensor system serves itself by finding sufficient features in natural scenes, eliminating the need for marker attachment and making the system versatile for unprepared objects.
Solution Approach 2:
The patent changes the detection parameter from requiring specific marker patterns to detecting natural visual feature changes. By adjusting the threshold parameter for event detection, the system can capture high-speed motion using naturally occurring visual changes in the scene, adapting to various objects without modification.
3Productivity
If multiple synchronized cameras are used to reduce standing still time, then capture speed increases, but data quantity and processing load increase
Solution Approach 1:
The event-based sensor system extracts only the necessary data points for 3D reconstruction by transmitting only pixels with significant intensity changes. This selective data extraction dramatically reduces the data quantity compared to full-frame capture from multiple cameras, while maintaining the ability to capture fast-moving objects at high speeds.
Solution Approach 2:
Instead of capturing complete frames at high speed (excessive action), the system captures only the essential change information (partial action) needed for reconstruction. This partial capture approach achieves high productivity by focusing computational resources only on meaningful data points rather than processing entire high-resolution frames.
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
Enables high-fidelity reconstruction of moving objects with low latency and high dynamic range, reducing data redundancy and computational requirements, while eliminating the need for markers, thus improving accuracy and applicability in dynamic scenarios.
Implementation Method 1
a plurality of imaging pixels each of which being capable to detect a light intensity on the imaging pixel, and to detect as an event a positive or negative change of the light intensity
Data Source
AI summary
A three-dimensional scanner system for reconstructing a three-dimensional shape of a moving object comprises a plurality of imaging devices each configured to be focused on the object and each comprising a plurality of imaging pixels each of which being capable to detect a light intensity on the imaging pixel, and to detect as an event a positive or negative change of the light intensity that is larger than a respective predetermined threshold, and a control unit configured to control the plurality of imaging devices and to reconstruct a time series of the three-dimensional shape of the object based on the events detected by the imaging devices and on additional information about colors, shape and/or movements of the object.