Automated POI Labeling via Image Feature Matching
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Solution Overview
Problem
Conventional methods for labeling points of interest (POIs) in images are labor-intensive, time-consuming, and costly, relying on manual verification which is inefficient and costly, especially when dealing with numerous POI categories.
Innovation Solution
A method and device that extract image features from images to be labeled and match them with reference images in a library based on similarity, automatically labeling the POIs using the category and location of the reference images, thereby improving efficiency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual verification methods are used for labeling POIs, then labeling accuracy can be maintained through human judgment, but labeling efficiency is severely reduced and costs increase
Solution Approach 1:
The patent uses reference images from an image library as templates to copy labeling information to similar images. By extracting features from the image to be labeled and comparing them with reference image features, the system automatically identifies matching references and transfers their POI labels, eliminating manual verification while maintaining consistency through the copying mechanism.
Solution Approach 2:
The patent replaces the mechanical manual verification process with an automated computer-based system. The system uses feature extraction algorithms, similarity comparison mechanisms, and automatic label transfer to substitute human operators, thereby dramatically improving labeling efficiency and reducing time loss.
2Productivity
If automated labeling methods are implemented, then labeling efficiency is improved, but labeling precision may deteriorate without manual verification
Solution Approach 1:
The patent implements a feedback mechanism where the system calculates similarity degrees between the image to be labeled and reference images, then uses this feedback to determine the most appropriate reference for label transfer. The feedback loop ensures that only highly similar images are matched, maintaining labeling accuracy while enabling automated processing.
Solution Approach 2:
The patent replaces manual verification with an automated feature-based matching system that uses image processing algorithms to compare visual characteristics. This substitution maintains precision by using objective feature extraction and similarity measurement rather than subjective human judgment, while dramatically improving efficiency.
3Manufacturing precision
If feature extraction and similarity matching are performed on all images, then labeling accuracy is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent extracts only the essential features needed for POI identification from images, rather than processing all image data. By taking out and focusing on key visual features relevant to point of interest recognition, the system reduces computational complexity while maintaining labeling accuracy through targeted feature comparison.
Solution Approach 2:
The patent applies feature extraction and similarity matching selectively to regions and characteristics most relevant to POI identification. By focusing computational resources on locally important features rather than uniformly processing entire images, the system reduces overall complexity while preserving accuracy where it matters most.
Data Source
AI summary
Embodiments of the present disclosure provide a method and device for labelling a point of interest, a computer device, and a storage medium. The method includes the following. Image data to be labelled is obtained. The image data includes an image to be labelled and a collection location of the image to be labelled. Feature extraction is performed on the image to be labelled to obtain a first image feature of the image to be labelled. A first reference image corresponding to the image to be labelled is determined based on a similarity between the first image feature and a second image feature corresponding to each reference image in an image library. The point of interest of the image to be labelled is labelled based on a category of the first reference image and the collection location of the image to be labelled.