Pointer Trace Image Labeling for AI Vision Training
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Solution Overview
Problem
The current image collection and labelling process for AI vision model training is complex, time-consuming, and provides a poor user experience, especially for data scientists who lack information about vehicle parts, making it difficult to label images effectively.
Innovation Solution
A method that captures a video of an object using a camera and records the movement trace of a pointer outlining the object, generating a labeled image with the object surrounded by a line, which simplifies the image collection and labelling process by allowing users to intuitively interact and label objects without the need for extensive knowledge or communication with data scientists.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a user manually takes images and uploads them to a labelling tool for data scientists to label, then the labeling process can be completed with basic equipment, but the process becomes complex and time-consuming
Solution Approach 1:
The patent combines image capture and labeling operations into a single integrated process. The camera device allows users to capture images and perform labeling operations (such as drawing bounding boxes or segmentation masks) directly on the captured images without separate upload and labeling steps, merging multiple operations into one unified workflow.
Solution Approach 2:
The system enables end-users to perform labeling operations themselves directly on the camera device or connected computing equipment. Users can draw bounding boxes, create segmentation masks, and annotate images without requiring data scientists to manually process each image, allowing the labeling task to serve itself through automated or semi-automated tools.
2Ease of operation
If data scientists label images without sufficient information about vehicle parts, then the labeling process can proceed without additional communication, but the labeling accuracy and effectiveness deteriorate
Solution Approach 1:
The patent introduces an information intermediary system that bridges the gap between users who capture images and data scientists who label them. This includes automated image analysis tools, part detection algorithms, and information display features that provide contextual data about vehicle parts directly to the labeling interface, enabling data scientists to make accurate labeling decisions without extensive prior knowledge or repeated communication cycles.
3Productivity
If multiple steps are involved in the image collection and labeling process, then each step can be performed with simple tools, but the overall process complexity increases
Solution Approach 1:
The camera device and associated software platform are designed as universal systems that perform multiple functions: capturing images, preprocessing images, enabling labeling operations, and exporting labeled data. This multi-functional integration reduces the need for separate specialized tools for each step of the workflow, simplifying the overall process while maintaining high productivity.
Data Source
AI summary
A method, a computing system and a computer program product for collecting and labelling images includes capturing a video of an object with a camera. A movement trace of a pointer is recorded that outlines the object while capturing the video of the object. Further included is generating a labeled image based at least on the captured video of the object and the recorded movement trace of the pointer. The labeled image includes the object and a line that surrounds the object.