Video Smoothness Evaluation Using Lens and Object Motion Vectors
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Solution Overview
Problem
Existing methods for evaluating video smoothness based on frame rate do not consider human vision, leading to low accuracy in assessing video quality.
Innovation Solution
Determine video smoothness by acquiring a target video, calculating motion vectors between frames, including lens and object motion vectors, and using a motion-smoothness mapping relationship to quantify smoothness based on human vision characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If frame rate is used to evaluate video smoothness, then the evaluation process is simple, but the accuracy of video smoothness determination is low
Solution Approach 1:
The patent transforms the evaluation from a single parameter (frame rate) to multiple parameters including lens motion vectors, object motion vectors, and their derivatives. This parameter expansion enables accurate reflection of human visual perception of smoothness while maintaining computational feasibility through standardized calculation procedures.
2Measurement precision
If motion estimation is performed to improve smoothness evaluation accuracy, then the accuracy of video smoothness determination is improved, but the computational complexity increases
Solution Approach 1:
The patent segments motion analysis into distinct components: lens motion vectors and object motion vectors. This segmentation allows independent calculation and processing of different motion types, reducing overall computational complexity while maintaining comprehensive evaluation accuracy.
Solution Approach 2:
The patent calculates only the essential motion parameters needed for smoothness evaluation (lens and object motion vectors and their derivatives) rather than performing complete frame analysis. This partial action approach achieves sufficient accuracy for smoothness assessment without unnecessary computational overhead.
Data Source
AI summary
A method, apparatus, device, and medium for determining video smoothness is provided. The method includes: acquiring a target video; determining a motion vector between different video frames by performing motion estimation on different video frames in the target video, the motion vector including a lens motion vector and an object motion vector, the lens motion vector indicates a position change of a lens between different video frames, and the object motion vector indicates a position change of the same photographed object in different video frames; and determining smoothness of the target video according to the motion vector between different video frames.