Picture Selection via Motion Feature Analysis
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Solution Overview
Problem
Current methods for selecting pictures in motion scenes, such as using burst shooting and video de-framing, suffer from low accuracy and differentiation, as they rely on features like definition and brightness that are not directly related to motion processes, leading to missed action moments and limited applicability.
Innovation Solution
A picture selection method that obtains feature information from a sequence of images, determines inter-frame information to identify feature change key points, and selects pictures based on these key points to capture moments of speed or rhythm changes, ensuring higher accuracy and differentiation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If burst shooting function is used to capture multiple pictures in motion scenes, then the quantity of captured pictures increases, but the accuracy of selecting key moment pictures decreases
Solution Approach 1:
The patent changes the selection parameters from static picture quality metrics (definition, brightness) to dynamic motion parameters (speed, acceleration, rhythm changes). By analyzing inter-frame information and detecting feature change key points based on motion dynamics, the system accurately identifies key moments among multiple captured pictures, resolving the contradiction between capturing more pictures and selecting accurate key moments.
2Adaptability or versatility
If video de-framing is used to obtain motion segments and select pictures, then the applicability to motion scenes improves, but the accuracy and differentiation of selected pictures deteriorates
Solution Approach 1:
The patent segments the motion process into distinct phases by detecting feature change key points where motion parameters (speed, acceleration, rhythm) exhibit significant changes. Each key point represents a distinct action phase, enabling accurate identification of key moments with high differentiation. This segmentation approach maintains high accuracy while being broadly applicable to various motion scenes.
3Ease of operation
If picture selection is based on definition and brightness features, then the selection process is simple, but the accuracy of capturing key action moments decreases
Solution Approach 1:
The patent transitions from static picture quality assessment to dynamic motion analysis by examining changes in motion parameters across frames. The system calculates speed, acceleration, and rhythm changes between consecutive frames to identify key moments, making the selection process adaptive to motion dynamics while maintaining computational efficiency through incremental calculations.
Data Source
AI summary
In a method for selecting pictures from a sequence of pictures of an object in motion, a computerized user device determines, for each picture in the sequence of pictures, a value of a motion feature of the object. Based on analyzing the values of the motion feature of the pictures in the sequence, the device identifies a first subset of pictures from the pictures in the sequence. The device then selects, based on a second selection criterion, a second subset of pictures from the first subset of pictures. The pictures in the second subset are displayed to a user for further selection.