Image Processing Device Best Shot Extraction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image processing technologies fail to efficiently and accurately extract frame images corresponding to the best shots from moving images, particularly in scenarios with multiple subjects or long shooting periods, leading to increased processing time and lower accuracy.
Innovation Solution
An image processing device and method that acquire moving and still images, extract characteristic information, detect target subjects, adjust image analysis conditions based on subject presence, and calculate evaluation values for frame images to rapidly and accurately identify best shots.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all persons in the moving image are tracked to ensure complete subject coverage, then extraction accuracy is improved, but processing time increases significantly
Solution Approach 1:
The patent segments the moving image into multiple time periods and divides the tracking task by identifying a representative person for each time period. Instead of tracking all persons throughout the entire image, the system selects one representative person per time period to track, significantly reducing processing time while maintaining extraction accuracy through the representative sampling approach.
Solution Approach 2:
The patent extracts only the necessary tracking information for representative persons rather than processing all persons in the moving image. By extracting and analyzing only the representative persons who characterize each time period, the system achieves accurate frame image extraction without the computational burden of tracking every individual present in the scene.
2Reliability
If frame images are extracted from the entire moving image to ensure comprehensive coverage, then extraction completeness is improved, but processing efficiency deteriorates
Solution Approach 1:
The patent segments the moving image into discrete time periods and extracts frame images only from representative persons within each time period. This segmented approach ensures comprehensive coverage of all time periods while avoiding redundant processing of non-representative persons, thereby improving processing efficiency without sacrificing extraction completeness.
Solution Approach 2:
The patent applies partial action by extracting frame images only from representative persons rather than all persons in the moving image. This selective extraction is sufficient to capture the essential characteristics of each time period, achieving the necessary completeness with reduced processing effort and improved efficiency.
3Measurement precision
If detailed image analysis is performed on all frame images to ensure high accuracy, then measurement precision is improved, but processing time increases
Solution Approach 1:
The patent applies local quality by performing detailed image analysis only on frame images extracted from representative persons rather than all persons. The analysis depth is localized to the representative samples, maintaining high measurement precision for the extracted frame images while avoiding the time-consuming detailed analysis of non-representative persons throughout the entire moving image.
Data Source
AI summary
In the image processing device, the method and the recording medium according to the present invention, the characteristic information extractor extracts the number of times the same subject appears in the still images. The target object detector detects the target subject which appears the number of times not less than the threshold value. The image analysis condition determiner sets the image analysis condition for the portion of the moving image where the target subject is absent to be rougher than that where the target subject is present. The frame image analyzer extracts frame images from the moving image in accordance with the image analysis condition. The frame image output section calculates the evaluation value of the frame images based on the result of the image analysis and output the frame image having the evaluation value not less than the threshold value.