Multimedia Summarization via Object Weight Prioritization
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Solution Overview
Problem
Existing video summarization technologies fail to maintain continuity by including significant characters or objects that remain inactive or quiet in multimedia content, as they provide equal weightage to all objects without considering their significance.
Innovation Solution
A method and system that identify primary objects and their interactions within multimedia content, prioritize parameters such as frequency and duration of appearance, and assign weights to determine the primary object of interest, allowing for summarization based on user interest or object relevance, ensuring continuity by retaining relevant scenes before and after the primary object.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If equal weightage is provided to all objects in video summarization, then the summarization process is simple and unbiased, but significant characters or objects that remain inactive are not included, leading to loss of continuity in the summary
Solution Approach 1:
The patent applies local quality by assigning different weights to different objects based on their significance rather than treating all objects equally. The system identifies primary objects of interest and assigns them higher weights, while secondary objects receive lower weights. This differentiated approach ensures that significant characters or objects are included in the summary even when they remain inactive, thereby maintaining continuity without requiring complex global restructuring of the summarization process
Solution Approach 2:
The patent changes the parameter of object weightage from a uniform value to a variable value based on object significance. By introducing parameters such as frequency of appearance, duration of appearance, and interaction with other objects, the system dynamically adjusts the weight assigned to each object. This parameter change enables the prioritization of significant objects while keeping the overall summarization framework relatively simple
2Measurement precision
If detailed analysis of every object is performed to identify significant characters, then the accuracy of summary is improved, but the processing time and computational resources increase significantly
Solution Approach 1:
The patent segments the video analysis process into distinct stages: initial object detection, parameter measurement (frequency and duration of appearance), interaction analysis, and weight assignment. By dividing the analysis into these manageable segments, the system can identify significant objects through multiple passes or incremental processing, reducing the computational burden compared to analyzing every object in detail simultaneously. This segmented approach maintains accuracy while managing processing time effectively
Solution Approach 2:
The patent implements partial action by focusing analysis primarily on primary objects that meet certain criteria (such as minimum frequency or duration thresholds) rather than performing exhaustive analysis on every object in the video. The system performs detailed measurement and analysis only on objects that are likely to be significant, while applying simpler heuristics or default treatments to less important objects. This selective approach maintains measurement precision for critical objects while significantly reducing overall processing time
Data Source
AI summary
This disclosure relates to a method and system for summarizing multimedia content. The method may include receiving multimedia content. The method may further include identifying one or more primary objects, wherein identifying the primary objects comprises identifying one or more actions associated with the primary objects and one or more interactions between the primary objects and one or more secondary objects. The primary objects are associated with one or more parameters. The method may further include determining at least one primary object of interest from the primary objects by selectively prioritizing the parameters. The method may further include summarizing the multimedia content based on the primary object of interest, actions associated with the primary object of interest, interactions between the primary object of interest and the secondary objects, and interactions between the secondary objects and one or more tertiary objects.