Image Analysis System for Change Detection Across Time and Position
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Solution Overview
Problem
Existing systems face challenges in efficiently analyzing and comparing images taken at different times to detect changes in scenes or objects, particularly with the advent of ubiquitous cellular devices equipped with imaging capabilities, which require efficient configuration for object analysis across varying locations, orientations, and time frames.
Innovation Solution
A method and system for analyzing images over time by capturing multiple images of specified objects in specified locations, identifying regions of interest, and comparing them across different locations, orientations, and timings to detect changes, utilizing techniques such as keypoint descriptors and GPU processing for efficient computation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple images are captured and compared across different locations, orientations, and time slots to detect changes, then the accuracy and comprehensiveness of change detection is improved, but the complexity of image alignment and comparison increases
Solution Approach 1:
The patent divides the image comparison process into distinct stages: capturing images at multiple time slots, identifying corresponding objects in each image, aligning images based on object positions, and then performing change detection. This segmentation allows each step to be optimized independently, managing complexity while maintaining high detection accuracy through systematic processing
Solution Approach 2:
The patent introduces keypoint descriptors and object recognition algorithms as intermediary tools that facilitate the comparison process. These intermediaries automatically identify corresponding objects across different images and establish alignment relationships, reducing the manual complexity of comparing images taken from different locations and orientations while improving detection accuracy
2Adaptability or versatility
If images are captured at different time slots and locations to monitor scene changes, then the coverage and monitoring capability are improved, but the computational resources and processing time required increase
Solution Approach 1:
The patent performs preliminary actions by pre-identifying objects of interest and establishing their spatial relationships before conducting full change detection. Images are pre-processed to extract key features and object positions, which are then used to guide the comparison process. This preliminary action reduces the computational burden during actual change detection while maintaining comprehensive monitoring coverage across multiple time slots and locations
Solution Approach 2:
The patent applies partial action by focusing computational resources only on regions containing objects of interest rather than processing entire images. By identifying and comparing only the relevant portions of images where changes are likely to occur, the system achieves comprehensive monitoring coverage while significantly reducing energy consumption and processing requirements
3Productivity
If automatic image analysis is performed to detect changes in scenes, then the productivity and efficiency of monitoring operations are improved, but the difficulty of configuring the system for diverse applications increases
Solution Approach 1:
The patent implements a universal image analysis framework that can be applied to multiple different applications and scenarios. The system uses general-purpose object recognition and change detection algorithms that can be configured for various purposes such as construction monitoring, environmental surveillance, or security applications. This universality maintains high productivity across diverse applications while reducing configuration difficulty through a standardized interface and common processing pipeline
Data Source
AI summary
A method of analyzing images over time is provided herein. The method includes: capturing a plurality of images each associated with specified objects in specified locations such that a specified area is covered; specifying regions of interest (ROI) in each of the captured images; repeating the capturing with at least one of: a different location, a different orientation, and a different timing such that the captured images are associated with the specified covered area; and comparing the captured imaged produced in the capturing with the captured imaged produced in the repeating of the capturing to yield comparison between the captured objects by comparing specified ROI.