Hyperlapse Video Reference-Point Matching for Stable Capture
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Solution Overview
Problem
Existing hyperlapse video generation methods often result in shaky and unsmooth videos due to misalignment of reference points, requiring manual user intervention that causes camera shaking and user fatigue, and post-capture editing cannot fully rectify these issues.
Innovation Solution
A processor-based method that automatically matches reference points between images or video frames, adjusts camera settings, and performs automatic shooting when alignment and horizontal conditions are met, reducing the need for manual user input and minimizing shaking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual user intervention is used to align reference points, then alignment accuracy is improved, but camera shaking and user fatigue increase
Solution Approach 1:
The system automatically identifies and matches reference points between consecutive images without requiring manual user intervention. The processor detects feature points, tracks their positions across frames, and autonomously determines alignment, allowing the system to serve itself rather than relying on user input that causes camera shaking.
Solution Approach 2:
The patent replaces the mechanical manual operation of aligning reference points with an automated computational image processing system. The processor uses algorithmic methods to detect, track, and match reference points, substituting human mechanical adjustment with automated digital processing to eliminate shaking caused by manual intervention.
2Measurement precision
If manual user intervention is used to align reference points, then alignment accuracy is improved, but shooting time increases due to user fatigue
Solution Approach 1:
The system performs automatic reference point matching without user intervention, enabling continuous automated shooting. The processor autonomously identifies, tracks, and matches reference points across multiple frames, allowing the system to operate independently and maintain alignment accuracy throughout extended shooting sequences without time loss to manual intervention.
Solution Approach 2:
The system pre-identifies and tracks reference points in advance during the shooting process, rather than requiring post-capture manual alignment. By performing reference point matching automatically as images are captured, the system prepares alignment data beforehand, eliminating time-consuming manual intervention and enabling seamless continuous shooting.
3Productivity
If automatic shooting is performed without reference point matching, then shooting speed is improved, but video quality deteriorates due to misalignment
Solution Approach 1:
The system continuously monitors reference point positions between consecutive images and uses this feedback to maintain proper alignment during automatic shooting. The processor compares reference point coordinates across frames, detects deviations, and adjusts tracking parameters in real-time, providing feedback control that ensures video quality is maintained throughout automated high-speed shooting sequences.
Solution Approach 2:
The patent replaces manual alignment operations with automated computational image processing that occurs at high speed. The processor uses algorithmic methods to detect and match reference points rapidly, substituting slow manual alignment with fast automated processing that maintains both shooting speed and video quality through precise digital alignment.
4Measurement precision
If post-capture editing is used to correct misalignment, then alignment accuracy is improved, but the shaking issues cannot be fully rectified
Solution Approach 1:
The system performs reference point matching and alignment correction during the capture phase rather than relying on post-capture editing. By automatically tracking and matching reference points in real-time as images are acquired, the system corrects alignment issues preliminarily, preventing shaking from occurring in the first place rather than attempting to rectify it after the fact.
Solution Approach 2:
The system autonomously performs alignment correction during shooting without requiring post-capture manual editing. The processor automatically detects reference points, calculates their positions, and corrects alignment deviations in real-time, allowing the system to self-correct misalignment issues during capture rather than relying on subsequent editing processes that cannot fully eliminate shaking.
Data Source
AI summary
A method of generating a hyperlapse video includes: comparing a first reference point of a first image and a corresponding second reference point of a second image; based on the comparing, displaying a first user interface for matching the first reference point and second reference point; and determining whether to perform automatic shooting for the hyperlapse video based on whether the first reference point and the second reference point match.