Multi-Camera Time Shift Alignment Using Landmark Coordinate Charts
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Solution Overview
Problem
Existing methods for synchronizing images captured by different cameras are inadequate when synchronization is performed at a later time, as the time shift between images is unknown, leading to unsatisfactory results, especially with moving objects or camera movement.
Innovation Solution
A time shift determination unit and method that utilize a computing device to detect landmarks in images, compile charts of mean landmark coordinates, perform shifts, and evaluate similarity measures to determine the time shift between sequences of images captured by different cameras.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If images are captured and stored in memory without real-time synchronization, then the flexibility and adaptability of the system is improved, but the time shift between images from different cameras becomes unknown, leading to poor stitching quality
Solution Approach 1:
The system performs preliminary actions by detecting landmarks and computing charts of mean coordinates before the actual stitching process. These pre-computed charts enable later determination of time shifts without requiring real-time synchronization during capture, thus maintaining flexibility while ensuring precision.
Solution Approach 2:
The patent introduces intermediary charts representing the progression of mean landmark coordinates as a mediator between the raw image data and the final synchronization. These charts enable indirect determination of time shifts through similarity measurement, resolving the contradiction between flexible capture and precise synchronization.
2Productivity
If known real-time synchronization methods are used for stored images, then the processing speed is improved, but the accuracy of time shift determination deteriorates because the time shift is unknown
Solution Approach 1:
The system performs preliminary computation of landmark coordinates and their mean values before the stitching process. This preliminary action enables accurate time shift determination later without requiring real-time processing during capture, thus maintaining both speed and accuracy.
Solution Approach 2:
The patent creates copies of the image data in the form of charts representing landmark coordinate progressions. These charts can be processed independently and stored, enabling accurate time shift determination through similarity measurement without requiring real-time synchronization, thus achieving both speed and precision.
3Adaptability or versatility
If time shift determination is performed after image capture, then the system flexibility is improved, but the complexity of the synchronization process increases
Solution Approach 1:
The patent segments the synchronization process into distinct modules: landmark detection, mean coordinate computation, chart generation, similarity measurement, and time shift determination. This segmentation reduces overall complexity by making each step independent and manageable, while maintaining the flexibility of delayed processing.
Solution Approach 2:
The charts representing mean landmark coordinate progressions serve as intermediaries that simplify the synchronization process. By using these intermediate representations, the complex task of synchronizing images from multiple cameras is broken down into manageable steps of chart generation and similarity comparison, reducing overall system complexity.
Data Source
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AI summary
Methods and system are herein provided for determining a time shift between images captured by means of different cameras. In one example, a time shift determination unit (200) comprises a computing device (210) comprising one or more processors (212) and a memory (214), wherein the computing device (210) is configured to determine a defined plurality of landmarks in each image of a first plurality of successive images of a defined environment (100) captured by means of a first camera (20-1), each landmark being defined by an x-coordinate and a y-coordinate in each of the respective images, determine the defined plurality of landmarks in each image of a second plurality of successive images of the defined environment (100) captured by means of a second camera (20-2), each landmark being defined by an x-coordinate and a y-coordinate in each of the respective images, for each image captured by means of the first camera (20-1) and the second camera (20-2), determine a mean x-coordinate or a mean y-coordinate for the defined plurality of landmarks in the image, compile a first chart representing a progression of the mean x-coordinate of the defined plurality of landmarks over the first plurality of successive images, and a second chart representing a progression of the mean x-coordinate of the defined plurality of landmarks over the second plurality of successive images, or compile a first chart representing a progression of the mean y-coordinate of the defined plurality of landmarks over the first plurality of successive images, and a second chart representing a progression of the mean y-coordinate of the defined plurality of landmarks over the second plurality of successive images, determine a similarity measure of the first chart and the second chart, perform a defined number of shifts of the second chart with respect to the first chart, wherein with each shift the second chart is shifted by a defined number of images, and for each shift of the plurality of shifts determine a similarity measure of the first chart and the shifted second chart, and evaluate the determined similarity measures in order to determine a time shift between the first plurality of successive images and the second plurality of successive images.