Multi-Camera Image Acquisition Using Eye-Position Camera Selection
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Solution Overview
Problem
Optical field video communication consumes significant computing resources and transmission bandwidth due to the large amount of data, and the limited number of viewpoints that can be viewed by a user limits the efficiency of image acquisition.
Innovation Solution
An image acquisition method that selects a subset of cameras based on the position information of the viewer's eyes to acquire images, reducing the number of cameras involved in real-time image acquisition and minimizing resource waste.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all N cameras acquire images simultaneously, then image acquisition completeness is improved, but computing power consumption and transmission bandwidth usage increase significantly
Solution Approach 1:
The patent segments the set of N cameras into a subset of K cameras (where K < N) that will actively acquire images, while the remaining N-K cameras remain inactive. This segmentation is based on eye position information to select only the necessary cameras, thereby reducing computing power consumption and transmission bandwidth usage while maintaining adequate image acquisition completeness for the viewer's viewing position.
Solution Approach 2:
Instead of having all N cameras perform the complete action of image acquisition simultaneously, the patent applies partial action by selecting only K cameras to perform the acquisition task. This partial action approach reduces resource consumption (computing power and bandwidth) while still providing sufficient image quality for the viewer's specific viewing position.
2Reliability
If all N cameras acquire images simultaneously, then image acquisition completeness is improved, but transmission bandwidth usage increases significantly
Solution Approach 1:
The patent segments the active camera set from the total camera set, selecting only K cameras out of N to acquire images based on eye position information. This segmentation reduces the quantity of image data that needs to be transmitted, thereby reducing transmission bandwidth usage while maintaining adequate image acquisition completeness for the viewer's viewing position.
Solution Approach 2:
The patent applies partial action by having only K cameras perform image acquisition instead of all N cameras. This reduces the total volume of image data generated and requires less transmission bandwidth, while still providing sufficient image quality for the viewer's specific viewing position.
3Loss of energy
If eye position information is used to select cameras, then computing power and bandwidth usage are reduced, but camera selection complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-dividing the N cameras into J triangular regions before actual image acquisition. When eye position information is received, the system only needs to determine which region the eyes are in and select cameras accordingly, rather than performing complex analysis of all camera positions relative to eye positions. This preliminary spatial organization simplifies the real-time camera selection process.
Data Source
AI summary
An image acquisition method applied to a first electronic device, and the first electronic device includes N first cameras, N being an integer greater than or equal to 3. The image acquisition method includes: firstly, receiving, by the first electronic device, first position information from a second electronic device, the first position information being position information of eyes of a viewer of the second electronic device; then, selecting, by the first electronic device, K first cameras from the N first cameras based on the first position information, K being an integer greater than or equal to 2 and less than N; then, acquiring, by the first electronic device, images by using the K first cameras.