Multi-Person Image Capture Using Composition Indicators
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Solution Overview
Problem
Existing image capture methods in electronic devices fail to consider the distribution of person weight and position relationships in multi-person scenarios, leading to picture imbalance and low image quality.
Innovation Solution
An image capture method that evaluates composition quality by quantifying parameters such as distance from a reference point, closeness between persons, and dispersion of positions, and stores frames with the highest composition quality, using face and human body detection to determine valid photographing statuses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If basic composition schemes are used to guide users in photographing, then users can obtain structured composition guidance, but the method does not consider person weight distribution and position relationships, leading to picture imbalance
Solution Approach 1:
The patent transforms subjective composition evaluation into objective quantitative parameters including distance parameter (matching degree with preset composition rules), closeness parameter (closeness degree between persons), and compactness parameter (dispersion degree of position arrangement). This parameter transformation enables precise measurement and comparison of composition quality across multiple frames
Solution Approach 2:
The system provides real-time feedback by calculating composition indicators for each captured frame and automatically selecting frames with highest composition quality. This closed-loop feedback mechanism guides the photographing process by continuously evaluating and comparing composition quality, enabling the system to identify and store optimal frames
2Manufacturing precision
If multiple frames of images are captured and filtered, then high composition quality images can be obtained, but the evaluation process becomes complex
Solution Approach 1:
The composition evaluation process is segmented into three independent parameter calculations: distance parameter evaluation (matching preset rules), closeness parameter evaluation (person-to-person distances), and compactness parameter evaluation (position dispersion). This segmentation allows each aspect to be calculated separately and then combined, simplifying the overall complex evaluation process
Solution Approach 2:
The patent introduces composition indicators as intermediary variables that bridge the gap between raw image data and quality evaluation. These indicators (distance parameter, closeness parameter, compactness parameter) serve as mediators that translate complex spatial relationships into comparable numerical values, simplifying the evaluation process
Data Source
AI summary
This application relates to the field of image technologies, and provides an image capture method and an electronic device. According to the method, images with high composition quality can be automatically captured. The method includes: displaying a plurality of frames of images captured by a camera in real time; determining a composition indicator of each frame of image based on person information in the corresponding image, where the person information includes a person quantity of target persons and one or more of a plurality of person parameters, the plurality of person parameters include a center of mass position of the target person, an area proportion of the target person, and a face position of the target person.