Accelerometer-Assisted Frame Synchronization for Mobile Camera Arrays
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Solution Overview
Problem
Achieving accurate frame synchronization in multi-camera setups is challenging due to differences in frame rates and trigger delays, often requiring expensive hardware solutions.
Innovation Solution
The system utilizes accelerometer data from IMU sensors in image-capture devices to determine relative offsets and synchronize frames through cross-correlation, enabling frame-accurate alignment without the need for expensive hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If expensive hardware synchronization devices are used, then frame synchronization accuracy is improved, but system cost increases
Solution Approach 1:
The patent replaces mechanical hardware synchronization devices with a software-based solution using accelerometer data from IMU sensors. The system captures acceleration data from multiple cameras, processes it through cross-correlation algorithms, and determines temporal offsets softwareually, eliminating the need for expensive hardware sync devices while maintaining synchronization accuracy.
Solution Approach 2:
The patent uses accelerometer data as a proxy or copy of the actual capture timing information. Instead of directly measuring precise capture times with hardware, the system captures acceleration data that correlates with camera movements and uses this copied signal to infer and correct temporal offsets between cameras.
2Manufacturing precision
If hardware synchronization devices are used, then frame alignment accuracy is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex hardware synchronization systems with software processing of accelerometer data. The solution uses cross-correlation algorithms to analyze acceleration signals from IMU sensors and compute temporal offsets, achieving precise frame alignment without additional hardware components.
Solution Approach 2:
The system uses the accelerometer data that is already captured by the IMU sensors in the camera system itself. The same sensors that track camera movement also provide the timing reference for synchronization, eliminating the need for separate synchronization hardware.
3Reliability
If multiple cameras capture simultaneously, then 3D reconstruction quality is improved, but synchronization difficulty increases
Solution Approach 1:
The patent introduces accelerometer data as an intermediary that mediates the synchronization between multiple cameras. The acceleration signals serve as a common reference that correlates with the capture timing of all cameras, enabling the system to compute and correct temporal offsets without direct hardware intervention.
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 method allows for cost-effective, accurate 3D volumetric capture by synchronizing frames across multiple cameras, improving the reliability of 3D reconstruction processes.
Implementation Method 1
Each video clip of the plurality of video clips may be acquired by a corresponding image-capture device of the plurality of image-capture devices in a moving state. The system may be configured to acquire, from the plurality of image-capture devices, a set of sensor data which corresponds to the plurality of image-capture devices and is associated with a movement of the plurality of image-capture devices.
Data Source
AI summary
A method and system for synchronization of image data is provided. A plurality of image-capture devices is controlled to acquire a plurality of video clips of at least one object. Each video clip of the plurality of video clips is acquired by a corresponding image-capture device of the plurality of image-capture devices in a moving state. From the plurality of image-capture devices, a set of sensor data is acquired. Such data corresponds to the plurality of image-capture devices and is associated with a movement of the plurality of image-capture devices. Thereafter, relative offsets between the set of sensor data are determined by using cross-correlation and matching frames in each of the plurality of video clips is further determined, based on the relative offsets.