Multi-Depth Image Generation via Tree Structure Interconnection

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Solution Overview

Problem

Existing methods for generating multi-depth images require manual selection and insertion of images, which is time-consuming and reduces productivity, as they do not provide an automated way to create these images by comparing multiple images.

Innovation Solution

A method that automatically generates a multi-depth image by selecting and interconnecting images through a tree structure based on similarities and feature points or objects, using feature point extraction algorithms and machine learning to determine image similarity and generate a hierarchical structure.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual selection and insertion of images is used to generate multi-depth images, then image quality and detail can be maintained, but productivity is reduced and the process becomes time-consuming

Engineering Contradiction:

Improvemulti-depth image generation speedVSAvoidtime for manual image selection and insertion

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system performs automatic image comparison and tree structure generation without requiring manual user intervention. The electronic device autonomously selects images, compares them using feature points, and constructs the hierarchical tree structure, enabling self-service operation that dramatically improves productivity while eliminating time loss associated with manual processes

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the manual mechanical process of image selection and insertion with an automated computational system. Machine learning algorithms and feature point comparison techniques substitute for human operators, automatically analyzing image similarities and generating the multi-depth image hierarchy, thereby resolving the contradiction between speed and time consumption

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If multiple images are compared and interconnected into a tree structure automatically, then productivity is enhanced, but device complexity increases due to image comparison algorithms

Engineering Contradiction:

Improveautomated multi-depth image generationVSAvoidimage comparison and tree structure generation system

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent segments the complex image processing task into distinct modules: feature point extraction, image comparison, similarity calculation, and tree structure construction. By dividing the overall process into separate functional components, the system manages complexity while maintaining high productivity in automated multi-depth image generation

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces feature points as an intermediary element that mediates between raw images and the final tree structure. Instead of directly comparing entire images which would be computationally intensive, the system extracts key feature points as intermediaries for comparison, simplifying the processing while preserving image relationship accuracy

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS11263477B2Method of auto-generation of multidepth image by interconnecting images into tree structure

Publication Date: 2022.03.01 PJ FACTORY CO LTD

AI summary

A method of automatically generating a multi-depth image is disclosed. According to at least one embodiment of the present disclosure,a method performed by an electronic device for generating a multi-depth image, includes selecting a plurality of images, interconnecting, through image comparisons of the plurality of images, at least some of the images into a tree structure, and generating the multi-depth image in which at least some of the images are hierarchically inserted in the tree structure by inserting a lower node image into an upper node image.