Hyperlapse Video Processing With ROI Tracking and Stabilization
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Solution Overview
Problem
Hyperlapse photography requires high stability, technical proficiency, and significant time investment, making it challenging for general users to create smooth hyperlapse videos without professional equipment and techniques.
Innovation Solution
An image processing method that determines an initial region of interest (ROI), performs object tracking and image stabilization on captured frames, and extracts partial image blocks based on an optimal field of view to generate hyperlapse videos.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional timelapse photography is used, then equipment complexity is reduced, but video smoothness and stability deteriorate
Solution Approach 1:
The patent replaces mechanical stabilization equipment (tripods, gimbals) with image processing-based stabilization. The system captures multiple images at different positions and uses algorithmic processing to compensate for movement, substituting physical mechanical stability with digital image processing to achieve smooth video output without requiring complex stabilization hardware
2Manufacturing precision
If manual positioning at multiple points is performed, then video quality is improved, but time consumption increases
Solution Approach 1:
The patent implements self-service through automated object tracking and ROI determination. The system automatically identifies and tracks the target object across multiple frames, dynamically adjusts the region of interest, and performs image stabilization without requiring manual intervention. This automation maintains high video quality while significantly reducing the time and effort previously required for manual positioning and processing
3Manufacturing precision
If professional filming techniques are used, then hyperlapse video quality is improved, but ease of operation deteriorates
Solution Approach 1:
The patent applies self-service by enabling the system to automatically perform complex filming tasks. The object tracking algorithm autonomously identifies and follows the target object, the ROI management system automatically adjusts the field of view, and the image stabilization processing automatically corrects for camera movement. This eliminates the need for users to master professional filming techniques while maintaining high hyperlapse video quality
Solution Approach 2:
The patent utilizes parameter changes to adapt the system to different shooting conditions. The object tracking algorithm dynamically adjusts tracking parameters based on motion detection, the ROI system automatically modifies region parameters to maintain optimal framing, and the stabilization process adapts correction parameters in real-time. This automatic parameter adjustment maintains professional-quality output without requiring users to manually tune complex parameters
Data Source
AI summary
An image processing method and an electronic device are provided. The method is adapted to the electronic device including an image capturing device. An initial region of interest (ROI) for enclosing a target object is determined, and an original video including multiple frames is captured through the image capturing device. Based on the initial ROI, an object tracking processing is performed on the frames to obtain an ROI in each frame. According to the ROI in each frame, an image stabilization processing is performed on each frame to obtain multiple corrected frames. Based on visible areas in the corrected frames, an optimal field of view is determined. A hyperlapse video is generated by extracting partial image blocks from each corrected frame according to the optimal field of view.