SketchPlay: Intuitive Creation of Physically Realistic VR Content with Gesture-Driven Sketching
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866918264106385408 |
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| author | Zhang, Xiangwen Dai, Xiaowei Chen, Runnan Chen, Xiaoming Hu, Zeke Zexi |
| author_facet | Zhang, Xiangwen Dai, Xiaowei Chen, Runnan Chen, Xiaoming Hu, Zeke Zexi |
| contents | Creating physically realistic content in VR often requires complex modeling tools or predefined 3D models, textures, and animations, which present significant barriers for non-expert users. In this paper, we propose SketchPlay, a novel VR interaction framework that transforms humans' air-drawn sketches and gestures into dynamic, physically realistic scenes, making content creation intuitive and playful like drawing. Specifically, sketches capture the structure and spatial arrangement of objects and scenes, while gestures convey physical cues such as velocity, direction, and force that define movement and behavior. By combining these complementary forms of input, SketchPlay captures both the structure and dynamics of user-created content, enabling the generation of a wide range of complex physical phenomena, such as rigid body motion, elastic deformation, and cloth dynamics. Experimental results demonstrate that, compared to traditional text-driven methods, SketchPlay offers significant advantages in expressiveness, and user experience. By providing an intuitive and engaging creation process, SketchPlay lowers the entry barrier for non-expert users and shows strong potential for applications in education, art, and immersive storytelling. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_22016 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | SketchPlay: Intuitive Creation of Physically Realistic VR Content with Gesture-Driven Sketching Zhang, Xiangwen Dai, Xiaowei Chen, Runnan Chen, Xiaoming Hu, Zeke Zexi Human-Computer Interaction Computer Vision and Pattern Recognition Creating physically realistic content in VR often requires complex modeling tools or predefined 3D models, textures, and animations, which present significant barriers for non-expert users. In this paper, we propose SketchPlay, a novel VR interaction framework that transforms humans' air-drawn sketches and gestures into dynamic, physically realistic scenes, making content creation intuitive and playful like drawing. Specifically, sketches capture the structure and spatial arrangement of objects and scenes, while gestures convey physical cues such as velocity, direction, and force that define movement and behavior. By combining these complementary forms of input, SketchPlay captures both the structure and dynamics of user-created content, enabling the generation of a wide range of complex physical phenomena, such as rigid body motion, elastic deformation, and cloth dynamics. Experimental results demonstrate that, compared to traditional text-driven methods, SketchPlay offers significant advantages in expressiveness, and user experience. By providing an intuitive and engaging creation process, SketchPlay lowers the entry barrier for non-expert users and shows strong potential for applications in education, art, and immersive storytelling. |
| title | SketchPlay: Intuitive Creation of Physically Realistic VR Content with Gesture-Driven Sketching |
| topic | Human-Computer Interaction Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2512.22016 |