Rotation Direction Detection Using Optical Flow Analysis
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Solution Overview
Problem
Current e-commerce platforms face challenges in efficiently determining the rotation direction of commodities in 360-degree rotating videos, as existing methods require complex hardware and fail to accurately detect the direction from uploaded videos.
Innovation Solution
A method and apparatus that input continuous video frames, establish a background model, perform foreground detection to determine the rotation axis center, and use optical flow analysis to determine the rotation direction, allowing for efficient detection and conversion of counterclockwise videos to clockwise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If master video of commodity is used to show multiple perspectives, then user viewing experience is improved, but occupied bandwidth increases too large
Solution Approach 1:
The patent extracts only the essential rotation direction information from the video data by analyzing optical flow characteristics. Instead of transmitting or processing complete master videos for all users, the system extracts rotation direction metadata to determine clipping strategies, significantly reducing bandwidth requirements while maintaining the ability to provide multi-perspective views when needed.
Solution Approach 2:
The patent creates simplified representations of the rotation information by analyzing optical flow patterns and generating rotation direction metadata. This copying approach allows the system to work with lightweight data structures rather than full video streams, enabling efficient bandwidth management while preserving the essential viewing experience.
2Measurement precision
If complex hardware is used to detect rotation direction, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex hardware-based rotation detection mechanisms with software-based optical flow analysis. By using computer vision algorithms to track pixel movements and infer rotation direction from video frames, the system achieves accurate rotation detection without requiring specialized sensors or mechanical detection devices, thereby reducing hardware complexity.
Solution Approach 2:
The patent introduces optical flow analysis as an intermediary process between video input and rotation direction determination. Instead of directly measuring rotation with complex hardware, the system uses optical flow fields as a mediator to translate visual information into rotation direction data, simplifying the overall detection system while maintaining accuracy.
Data Source
AI summary
The present disclosure relates to a method and apparatus for determining a target rotation direction. Said method for determining the target rotation direction comprises: inputting successive video frames which comprise a rotation target; establishing a background model for the first image frame in said video frames; performing foreground detection on the video frames other than the first frame by means of said background model so as to determine the rotation axis of said rotation target; obtaining the distribution of optical flow points within a preset region of said rotation axis; determining the direction of rotation of said rotation target according to the distribution of optical flow points within said preset region. By means of the present disclosure, it is possible to simply and efficiently determine the clock direction of a rotation target in a video.