Automatic Video Highlight Detection via Frame Difference Summation
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Solution Overview
Problem
Current methods lack an efficient way to automatically identify and select exciting segments from a video, as users need to manually preview and determine these segments, which is time-consuming and inefficient.
Innovation Solution
A method that calculates the difference between adjacent frames using image features like histogram-based pixel distributions, sums these differences for groups of frames, and selects segments with high sums as exciting segments, allowing for automatic determination and combination of overlapping or closely spaced groups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual preview and determination of exciting segments is used, then users can identify highlights, but it is time-consuming and inefficient
Solution Approach 1:
The system performs automatic determination of exciting segments without requiring user intervention. The processor automatically calculates frame differences, identifies groups with high sums, and selects exciting segments autonomously, eliminating the need for manual preview and significantly improving efficiency
Solution Approach 2:
The patent replaces the manual mechanical process of previewing and determining exciting segments with an automated computational system. The processor uses algorithmic calculations of frame differences and histogram comparisons to automatically identify highlights, substituting human manual operation with automated image processing
2Productivity
If automatic determination method is implemented, then efficiency is improved, but system complexity increases
Solution Approach 1:
The patent divides the video into groups of frames and processes each group independently. By segmenting the video content and handling frames in manageable groups rather than processing the entire video as one unit, the system achieves automation while keeping the computational complexity at each stage manageable
Solution Approach 2:
The system uses histogram-based image features with bins representing color component distributions. By transforming the problem into parameter space (histogram bins) and comparing these parameters between frames, the patent simplifies the complexity of direct pixel-level comparison while maintaining automation capability
Data Source
AI summary
A method is provided to automatically determine “exciting” segments from a video. The method includes calculating image features of each frame in the video, determining a difference for each pair of adjacent frames, calculating a sum of differences for each group of frames in the video, and selecting a number of the groups with high sums as exciting segments of the video. The differences between pairs of adjacent frames are used as a criterion for measuring a degree of “excitement” for determining the highlights in the video.