Camera Time-Shift Alignment Using Landmark Coordinate Progressions
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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 from multiple cameras, compile charts of mean landmark coordinates, perform shifts, and evaluate similarity measures to determine the time shift between sequences of images, enabling accurate synchronization before stitching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If images are stored in memory and stitching is performed at a later point in time, then flexibility and storage capability are improved, but time shift between images from different cameras cannot be determined leading to poor synchronization quality
Solution Approach 1:
The patent applies preliminary action by detecting landmarks and creating progressions of mean coordinates from image sequences before the actual stitching operation. This pre-processing establishes a foundation for later time shift determination, allowing the system to store images flexibly while maintaining the capability to accurately synchronize them when needed. The landmark detection and progression creation are performed in advance, enabling subsequent time shift calculation without requiring real-time processing during stitching.
2Reliability
If real time synchronization is performed, then time shift is minimized, but the method is not suitable for post-stored image processing where synchronization is done later
Solution Approach 1:
The system performs preliminary landmark detection and progression creation from stored images, enabling efficient later synchronization. By pre-processing the images to extract landmark information and establish coordinate progressions, the system avoids the need for computationally intensive real-time processing during the actual stitching operation, thus improving productivity while maintaining reliability.
Solution Approach 2:
The patent creates a copy of the essential synchronization information through landmark coordinates and their progressions. Instead of processing entire high-resolution images for synchronization, the system works with extracted landmark data, which is a simplified representation that contains the necessary temporal alignment information. This copying approach significantly reduces computational load while preserving synchronization accuracy.
3Measurement precision
If landmark detection and chart compilation is performed for all images, then time shift determination accuracy is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent extracts only the essential information needed for time shift determination by detecting specific landmarks and computing their mean coordinates, rather than processing entire images. This extraction approach isolates the critical temporal alignment data from the overwhelming amount of image data, significantly reducing computational complexity while maintaining the precision needed for accurate time shift determination.
Solution Approach 2:
The system transforms image data into a different parameter space by converting spatial coordinates of landmarks into temporal progressions. This parameter change from raw image pixels to landmark coordinate sequences simplifies the data structure and enables efficient comparison across different image sequences, reducing computational complexity while preserving the information necessary for accurate synchronization.
Data Source
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 comprises a computing device comprising one or more processors and a memory, wherein the computing device is configured to determine a defined plurality of landmarks in each image of a first plurality of successive images of a defined environment captured by means of a first camera, 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 captured by means of a second camera, 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 and the second camera, 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.