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DifferSketching: How Differently Do People Sketch 3D Objects?

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

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Abstract

Multiple sketch datasets have been proposed to understand how people draw 3D objects. However, such datasets are often of small scale and cover a small set of objects or categories. In addition, these datasets contain freehand sketches mostly from expert users, making it difficult to compare the drawings by expert and novice users, while such comparisons are critical in informing more effective sketch-based interfaces for either user groups. These observations motivate us to analyze how differently people with and without adequate drawing skills sketch 3D objects. We invited 70 novice users and 38 expert users to sketch 136 3D objects, which were presented as 362 images rendered from multiple views. This leads to a new dataset of 3,620 freehand multi-view sketches, which are registered with their corresponding 3D objects under certain views. Our dataset is an order of magnitude larger than the existing datasets. We analyze the collected data at three levels, i.e., sketchlevel, stroke-level, and pixel-level, under both spatial and temporal characteristics, and within and across groups of creators. We found that the drawings by professionals and novices show significant differences at stroke-level, both intrinsically and extrinsically. We demonstrate the usefulness of our dataset in two applications: (i) freehand-style sketch synthesis, and (ii) posing it as a potential benchmark for sketch-based 3D reconstruction. Our dataset and code are available at https://chufengxiao.github.io/DifferSketching/.
© 2022 Association for Computing Machinery
Original languageEnglish
Article number264
JournalACM Transactions on Graphics
Volume41
Issue number6
Online published30 Nov 2022
DOIs
Publication statusPublished - Dec 2022
Event15th ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia (SIGGRAPH Asia 2022) - Daegu Exhibition & Convention Center (EXCO), Daegu, Korea, Republic of
Duration: 6 Dec 2022 → 9 Dec 2022
https://sa2022.siggraph.org/en/

Funding

The work was supported by an unrestricted gift from Adobe, and grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (No. CityU 11212119), City University of Hong Kong (No. 9229094), Beijing Nova Program of Science and Technology (No. Z191100001119077), and the Centre for Applied Computing and Interactive Media (ACIM) of School of Creative Media, CityU.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Research Keywords

  • sketch dataset
  • freehand drawing
  • 3D reconstruction
  • sketch analysis
  • stroke analysis
  • DRAW

Publisher's Copyright Statement

  • COPYRIGHT TERMS OF DEPOSITED POSTPRINT FILE: © ACM 2022. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Graphics, https://doi.org/10.1145/3550454.3555493.

RGC Funding Information

  • RGC-funded

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