Non-greedy Hierarchical Video Segmentation
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Solution Overview
Problem
Existing video editing techniques fail to optimally divide videos into segments while maintaining hierarchical integrity, often resulting in sub-optimal divisions due to greedy merging or splitting methods that neglect overall hierarchy optimization.
Innovation Solution
A method for processing multiple candidate segmentation point sets to create alternative segmentation point sets with a specific number of points, where each point corresponds to the greatest counts, and arranging these in a hierarchical view to preserve optimal divisions across levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If greedy merging or splitting methods are used to divide videos into segments, then the segmentation process is simplified and faster, but the hierarchical integrity is compromised and sub-optimal divisions occur
Solution Approach 1:
The patent divides the video segmentation problem into multiple hierarchical levels, where each level represents a different granularity of segmentation. Instead of performing a single greedy segmentation, the system performs segmentation at multiple levels (e.g., coarse-grained segments first, then finer-grained subdivisions), allowing optimal divisions to be identified at each level while maintaining hierarchical integrity across all levels.
Solution Approach 2:
The patent implements a dynamic programming approach where the segmentation solution at each level depends on and builds upon the solutions from previous levels. The algorithm dynamically adjusts segmentation points across hierarchical levels, ensuring that divisions made at higher levels are preserved and optimized at lower levels, rather than using static greedy decisions that cannot be revised.
2Stability of the object's composition
If divisions at higher hierarchical levels are preserved at lower levels, then hierarchical integrity is maintained, but the flexibility to optimize each level independently is reduced
Solution Approach 1:
The patent structures the segmentation hierarchy as nested levels, where segments at higher levels are preserved and contained within segments at lower levels. Each hierarchical level is nested within the previous level, ensuring that divisions made at higher levels are maintained at lower levels while allowing additional optimization points to be introduced at each subsequent level.
Solution Approach 2:
The patent performs preliminary segmentation at higher hierarchical levels before proceeding to lower levels. By establishing the coarse-grained structure first and preserving those divisions, the algorithm creates a stable foundation that guides subsequent finer-grained segmentation, ensuring hierarchical integrity while still allowing optimization at each level.
3Manufacturing precision
If multiple candidate segmentation point sets are processed to ensure optimal divisions, then segmentation accuracy is improved, but the computational complexity increases
Solution Approach 1:
The patent processes multiple candidate segmentation point sets by dividing them into hierarchical levels, where each level handles a specific number of segments. This segmentation of the candidate sets allows the system to evaluate multiple options at each level without having to simultaneously process all candidates across all levels, reducing the computational burden while maintaining accuracy.
Solution Approach 2:
The patent uses dynamic programming to efficiently evaluate multiple candidate segmentation points by building solutions incrementally across hierarchical levels. Instead of evaluating all possible combinations of segmentation points simultaneously (which would be computationally exhaustive), the algorithm dynamically constructs optimal solutions level by level, reusing computations from previous levels to reduce overall complexity.
Data Source
AI summary
Segmenting serial data by processing multiple candidate segmentation point sets associated with a serial data set, each candidate set including a different number of candidate segmentation points representing the serial data set as segments in accordance with segmentation criteria, where the processing includes determining, for each of the candidate points, a count of the candidate sets that include the candidate point, and creating, for each of the candidate sets, a corresponding alternative segmentation point set associated with the serial data set, where the alternative set includes n alternative segmentation points representing the serial data set as n+1 segments, where n equals the number of candidate points in the candidate set to which the alternative set corresponds, and where the n alternative points in the alternative set correspond to n of the candidate points having the greatest counts, and arranging the alternative sets in order of their numbers of segmentation points.