AI Camera Buffering for User-Intended Image Capture
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Solution Overview
Problem
Existing image capturing systems rely heavily on user input, making it difficult to obtain high-quality images at the intended moment due to delays and shaking during manipulation.
Innovation Solution
An electronic device equipped with a camera, memory, and processor, utilizing two artificial intelligence modules to receive information about the image capturing situation, obtain target images, extract feature information, and store images related to this information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If user manipulation is used to trigger image capture, then the user can control when to capture, but delay and shaking during manipulation prevent obtaining high-quality images at the intended moment
Solution Approach 1:
The system performs preliminary actions by continuously capturing images before the user's intended capture moment and storing them in a buffer. When the user triggers the capture function, the system immediately selects and captures pre-captured images from the buffer that correspond to the intended moment, eliminating delay and shaking issues while maintaining user control.
2Extent of automation
If AI-driven autosuggestion technology is used to capture images based on predetermined criteria, then images can be captured automatically, but the system has difficulty reflecting each user's unique taste
Solution Approach 1:
The system incorporates feedback mechanisms where users can provide feedback about captured images, and the AI model uses this feedback to refine and update its understanding of user preferences. This allows the automated capture system to adapt to each user's unique taste over time while maintaining high automation levels.
3Device complexity
If existing single-take mode is used for video capture, then the pipeline remains simple, but it cannot effectively capture user-intended moments with specific feature information
Solution Approach 1:
The system segments the capture pipeline into distinct functional modules: a simple single-take mode pipeline for basic video capture, and a separate AI-driven module for capturing user-intended moments with specific features. This segmentation allows the existing simple pipeline to remain unchanged while adding sophisticated capture capabilities through a complementary AI-based subsystem.
Data Source
AI summary
The disclosure relates to an artificial intelligence (AI) system that simulates a function, such as cognition and judgment, of a human brain using a machine learning algorithm, such as deep learning, and an application thereof. According to an embodiment, an electronic device may include a touchscreen, a camera, a memory, and a processor, wherein the processor may receive information about an image capturing situation from a user, may obtain a target image based on the information about the image capturing situation using a first artificial intelligence module stored in the memory, may obtain feature information included in the target image using a second artificial intelligence module stored in the memory, may store the feature information in the memory, and may store an image related to the feature information in the memory based on obtaining the image related to the feature information through the camera.