Speed Labeling: Non-stop Scrolling for Fast Image Labeling
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| Chia-Ming Chang Yi Tang Xi Yang Xiang ’Anthony’ Chen Takeo Igarashi |
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| Abstract |
| This study presents “Speed Labeling”, an image-labeling technique to increase the efficiency of easy binary labeling tasks where an annotator can choose a label instantly. We first conduct a formative study to identify the factors affecting the efficiency of easy image labeling: image layout and image transition. Based on these results, we designed a novel labeling technique using non-stop scrolling. In conventional image labeling, the system moves to the next image only after the user assigns a label to the previous image. To maximize efficiency, our technique continuously scrolls images without waiting for the completion of labeling, assuming that the user gives labels at a mostly constant speed. The system dynamically adjusts the scrolling speed based on the labeling speed. Subsequently, we conduct a user study to compare the proposed “non-stop scrolling” technique to the conventional “stop-and-go scrolling” technique in an easy image-labeling task. The results showed that speed labeling requires less time (faster by 7%, 305 more images labeled per man-hour) to complete the labeling task than the conventional technique without a significant increase in errors. In addition, the results showed that speed labeling makes the labeling task more enjoyable for crowd workers and makes them feel more attentive during tasks. |
| Video [2m27s] |
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| Publication |
| Chia-Ming Chang, Yi Tang, Xi Yang, Xiang ’Anthony’ Chen and Takeo Igarashi, 2024. Speed Labeling: Non-stop Scrolling for Fast Image Labeling. The 50th International Conference on Graphics Interface and Human-Computer Interaction (Gl 2024), Halifax, Nova Scotia, Canada, 3-6 June 2024. [PDF] |
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| See more related works at "Labeling +" project. |
| Copyright © 2024 Chia-Ming Chang |