Object Dimension Estimation Using Vanishing Point Calibration
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Solution Overview
Problem
Surveillance systems face challenges in providing advance and preventive warnings due to reliance on manual identification of video images, and existing automatic analysis methods lack accuracy and efficiency in obtaining object dimensions from images.
Innovation Solution
A method and system that receive coordinates of feature points and reference objects with known dimensions, perform calibration to adjust these coordinates, and determine the dimension of target objects using vanishing points and optimal space calibration to increase accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual identification is used for recognition of video images, then system complexity is reduced, but productivity and response time deteriorate
Solution Approach 1:
The patent replaces manual identification (mechanical human operation) with an automatic computer-based analysis system that uses image processing algorithms to detect objects, extract features, and measure dimensions automatically, thereby eliminating the need for manual intervention while significantly improving productivity
Solution Approach 2:
The system enables self-service by automatically performing object detection, feature extraction, and dimension measurement without requiring manual operation. The computer system processes video images autonomously, identifying objects and calculating their dimensions through programmed algorithms
2Extent of automation
If traditional computer analysis methods are used to obtain object dimension, then automation is achieved, but measurement precision deteriorates
Solution Approach 1:
The patent applies preliminary calibration actions by establishing reference relationships between image coordinates and real-world dimensions before actual measurements are performed. This pre-calibration process creates a transformation model that significantly improves measurement precision in subsequent automated analysis
Solution Approach 2:
The system changes parameters by using multiple feature points and calibration references to establish accurate coordinate transformations. By adjusting and optimizing the calibration parameters based on known reference objects, the system achieves high measurement precision while maintaining full automation
3Device complexity
If feature points are not calibrated, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent introduces calibration references as intermediary elements that mediate between the image coordinate system and the real-world measurement system. These references serve as a bridge, enabling accurate dimension estimation by providing known geometric relationships that can be used to calibrate feature point coordinates
Data Source
AI summary
A system and a method of obtaining a dimension of a target object in an image comprises receiving coordinates of a number of feature points in the image, receiving coordinates of at least one reference object in the image with a known dimension, performing a calibration to adjust the coordinates of at least one of the feature points, and receiving coordinates of the target object in the image and determining the dimension of the target object based on the coordinates of the feature points. The coordinates of at least one of the feature points are adjusted to increase an accuracy in determining the dimension of the reference object.