Image Object Contour Guidance for Accurate Crowdsourced Labeling
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Solution Overview
Problem
Workers in crowdsourcing tasks face challenges in accurately setting the regions of objects in images, leading to deteriorated data quality and increased labeling time, as they lack clear guidelines for the required precision.
Innovation Solution
A method and system that generates and displays guide information on the image to help workers set object regions accurately by inputting contour information, using a closed curve with adjustable guide information inside the contour to indicate the required precision level.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If workers set regions of objects in images without clear guidelines, then labeling speed increases, but data quality deteriorates
Solution Approach 1:
The patent introduces guide information as an intermediary element between the worker and the object region. This guide information includes reference contours, distance indicators, and visual cues that mediate the worker's understanding of the required precision level, enabling accurate labeling without requiring extensive training or experience
Solution Approach 2:
The system performs preliminary actions by pre-calculating and displaying guide information before the worker completes the labeling task. This includes pre-determining the acceptable region boundaries, computing distance metrics, and rendering visual guides that prepare the worker in advance with all necessary precision criteria
2Manufacturing precision
If workers precisely set regions of objects, then data quality improves, but labeling time increases
Solution Approach 1:
The patent replaces the manual trial-and-error process with an automated guide information generation system. Instead of workers repeatedly adjusting regions to achieve precision, the system automatically computes and displays the correct boundaries and precision requirements, substituting mechanical adjustment with intelligent guidance
Solution Approach 2:
The system creates simplified copies or representations of the acceptable region boundaries through guide information. These visual copies include reference contours and boundary indicators that workers can directly follow, eliminating the need for complex judgment and repeated adjustments
3Measurement precision
If workers are provided with detailed guidelines for region setting, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent applies local quality by providing different types of guide information in different contexts. The system analyzes each image and object individually, generating customized guide information such as distance indicators for some objects, reference contours for others, and varying levels of detail based on the specific labeling task requirements
Solution Approach 2:
The system dynamically changes parameters of the guide information based on the specific image and object characteristics. This includes adjusting the level of detail, the type of visual cues displayed, and the precision requirements shown, all controlled by configurable parameters that can be adjusted without changing the underlying system architecture
Data Source
AI summary
The present invention relates to a method, a computing device, and a computer-readable medium for providing guide information on contour information of an object included in an image in crowdsourcing, and more particularly, to a method, a computing device, and a computer-readable medium for providing guide information on contour information of an object included in an image in crowdsourcing, in which guide information for a region set by a worker is generated and displayed on an image when the worker receiving the image corresponding to a work through the crowdsourcing performs labeling of setting the region of the object included in the image, thereby providing a guide on an accurate level required to be set for the region of the object.