Take-off Capture Method for Jumping Posture Selection
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Solution Overview
Problem
Existing mobile devices struggle to capture images of users in the best take-off posture during jumping due to timing mismatches and internal camera delays, requiring multiple attempts and manual selection from continuous images.
Innovation Solution
A take-off capture method that enters a capture mode upon detecting an image capturing operation, acquires image frames within a designated duration, filters the best image frame based on acquired frames using sliding windows and content recognition, and outputs a take-off capture image, ensuring the image is taken at the highest point of jump.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous image capturing is performed to capture take-off images, then the probability of capturing the best take-off posture increases, but the loss of time and increase in memory usage worsen
Solution Approach 1:
The system performs preliminary actions by pre-calculating exposure parameters and pre-warming the camera sensor before actual image capture. This preparation ensures that when the capture moment arrives, the camera is ready immediately, eliminating delays and reducing the need for multiple capture attempts, thus saving time while maintaining high capture success rate.
Solution Approach 2:
The system implements self-service through automated frame selection algorithms that automatically identify and select the optimal image frame from captured sequences based on take-off detection. This eliminates manual review and selection by users, reducing the time needed to obtain the final capture while ensuring high reliability through algorithmic optimization.
2Reliability
If multiple image frames are captured to ensure best posture, then capture reliability improves, but device complexity and calculation requirements increase
Solution Approach 1:
The system extracts only the essential and most relevant image frames from the captured sequence by using take-off detection algorithms to identify frames where the subject is actually in the take-off posture. This extraction process filters out unnecessary frames, reducing processing complexity while maintaining high capture success rate by focusing computational resources only on relevant frames.
Solution Approach 2:
The system changes parameters dynamically by adjusting exposure settings, frame rate, and processing intensity based on detected take-off conditions. When take-off is detected, the system increases frame capture rate and processing priority; otherwise, it reduces these parameters to minimize computational load and device complexity while ensuring reliable capture when needed.
3Ease of operation
If automated frame selection is implemented to reduce manual selection, then ease of operation improves, but measurement precision and filtering accuracy face challenges
Solution Approach 1:
The system implements feedback mechanisms where the automated frame selection algorithm continuously monitors capture results and user selections. When users manually select or reject frames, this feedback is used to refine and adjust the automated selection criteria, improving measurement precision over time while maintaining ease of operation through progressive optimization of the selection algorithm.
Solution Approach 2:
The system segments the frame selection process into multiple independent stages: initial automated selection based on take-off detection, followed by optional user review of shortlisted frames, and final confirmation. This segmentation allows automated processing to handle routine selections (improving ease of operation) while preserving user control for critical decisions (maintaining measurement precision).
Data Source
AI summary
A take-off capture method includes: acquiring, in response to obtaining an image capturing operation triggered by a user prior to taking off, image frames within a designated duration, upon entering a take-off capture mode; filtering at least one designated image frame based on the acquired image frames, the designated image frame being an image frame where the user is at a take-off high point within the designated duration; and performing an image capturing operation and outputting a take-off capture image based on the designated image frame, when an acquiring time period does not reach the designated duration but the designated image frame is filtered based on the acquired image frames, or when an acquiring time period reaches the designated duration. The user can therefore easily and quickly obtain the take-off capture image with the best take-off posture captured by the user in the take-off process.