@inproceedings{
zhang2024scenephotographer,
title={ScenePhotographer: Object-Oriented Photography for Residential Scenes},
author={Shao-Kui Zhang and Hanxi Zhu and Xuebin Chen and Jinghuan Chen and Zhike Peng and Ziyang Chen and Yong-Liang Yang and Song-Hai Zhang},
booktitle={ACM Multimedia 2024},
year={2024},
url={https://openreview.net/forum?id=ByZ5zuZC6X}
}
Humans understand digital 3D scenes by observing them from reasonably placed virtual cameras. Selecting camera views is fundamental for 3D scene applications but is typically manual. Existing literature on selecting views is based on regular or polygonal room shapes without focusing on the objects in the scene, resulting in poorly composed views concerning objects. This paper introduces ScenePhotographer, an object-oriented framework for automatic view selection in residential scenes. Potential object-oriented views are yielded by a learning-based method, which clusters objects into groups according to objects' functional and spatial relationships. We propose four criteria to evaluate the views and recommend the best batch, including room information, visibility, composition balance, and line dynamics. Each criterion measures the view according to its corresponding photography rule. Experiments on various room types and layouts demonstrate that our method can generate views focusing on coherent objects while preserving aesthetics, leading to more visually pleasing results.
ScenePhotographer: Object-Oriented Photography for Residential Scenes
Shao-Kui Zhang Hanxi Zhu Xuebin Chen Jinghuan Chen Zhike Peng Ziyang Chen Yong-Liang Yang Song-Hai Zhang