Visual Content Ambiguity Reduction via Functional Proximity Scoring
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Visual content, such as images and videos, often suffers from functional ambiguity due to subjective interpretation by viewers, which increases with the amount of content and is exacerbated by the lack of creator-user synchronization in space and time.
Innovation Solution
A method and system that identify objects in images, determine spatial and functional proximity scores, and associate domains with functionalities to reduce ambiguity by using object and knowledge repositories, processing these scores to generate a text summary that aligns with user profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If visual content is created based on creator's perception and knowledge, then the creator can convey a specific message, but the viewer's interpretation varies leading to functional ambiguity
Solution Approach 1:
The patent introduces an intermediary system that includes object repositories, knowledge repositories, and processing modules. This intermediary automatically analyzes visual content, identifies objects, determines their functionalities, and generates structured descriptions that bridge the gap between creator intent and viewer interpretation, reducing functional ambiguity without losing the adaptability of visual content
Solution Approach 2:
The system implements feedback mechanisms where user interactions, corrections, and annotations are captured and used to refine the object and knowledge repositories. This continuous feedback loop improves the accuracy of functional descriptions over time, ensuring that the system learns from varying user perspectives while maintaining message accuracy
2Quantity of substance
If the amount of visual content increases, then more information can be communicated, but subjectivity and ambiguity also increase
Solution Approach 1:
The patent segments visual content into discrete objects, each with identified functionalities and associations. By breaking down complex images into individual objects and their relationships, the system can process and describe large volumes of content systematically, maintaining message clarity even as content volume increases
Solution Approach 2:
The system changes the parameter of content description from subjective human interpretation to objective structured data with measurable attributes such as spatial proximity scores, functional proximity scores, and domain scores. This parameter transformation enables consistent processing of large content volumes while preserving message accuracy
3Adaptability or versatility
If creator and user are not in the same space and time, then content can be shared more broadly, but ambiguity in interpretation increases
Solution Approach 1:
The patent creates structured digital copies of visual content that include embedded object identities, functionalities, and relationships. These copies can be transmitted and processed anywhere in the system without requiring the original creator's presence, maintaining interpretation accuracy through the embedded structured information while enabling broad accessibility
4Loss of information
If detailed object identification and domain association are performed, then functional ambiguity is reduced, but system complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-organizing objects and their functionalities in object repositories, and pre-establishing domain knowledge in knowledge repositories. This preliminary structuring enables the system to quickly associate objects with domains without complex real-time processing, reducing functional ambiguity while managing system complexity through advance preparation
Data Source
AI summary
The present disclosure relates to a method and a system for reducing functional ambiguity from an image. In one embodiment, an input image is received and processed to identify objects. Spatial proximity score of the identified objects are determined based on which functional proximity score of functionalities associated with the identified objects is further determined. Upon determining the functional proximity score, possible domain of all the functionalities associated with the identified objects is determined. Further, a domain score is determined based on which the ambiguity of the domain related to the input image is reduced. A text summary of objects, functionalities and possible domains associated with the input image is then generated upon mapping with one or more user profiles and displayed to end user.


