Data-driven contextual modeling for 3D scene understanding
文献类型：期刊论文
| 作者 | Yifei Shi; Pinxin Long; Kai Xu; Hui Huang; Yueshan Xiong |
| 刊名 | Computers & Graphics
 |
| 出版日期 | 2016 |
| 英文摘要 | The recent development of fast depth map fusion technique enables the realtime, detailed scene reconstruction using commodity depth camera, making the indoor scene understanding more possible than ever. To address the specific challenges in object analysis at subscene level, this work proposes a data-driven approach to modeling contextual information covering both intra-object part relations and inter-object object layouts. Our method combines the detection of individual objects and object groups within the same framework, enabling contextual analysis without knowing the objects in the scene a priori. The key idea is that while contextual information could benefit the detection of either individual objects or object groups, both can contribute to object extraction when objects are unknown. |
| 收录类别 | SCI |
| 原文出处 | http://www.sciencedirect.com/science/article/pii/S0097849315002009 |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/10167]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 作者单位 | Computers & Graphics |
| 推荐引用方式 GB/T 7714 | Yifei Shi,Pinxin Long,Kai Xu,et al. Data-driven contextual modeling for 3D scene understanding[J]. Computers & Graphics,2016. |
| APA | Yifei Shi,Pinxin Long,Kai Xu,Hui Huang,&Yueshan Xiong.(2016).Data-driven contextual modeling for 3D scene understanding.Computers & Graphics. |
| MLA | Yifei Shi,et al."Data-driven contextual modeling for 3D scene understanding".Computers & Graphics (2016). |
入库方式： OAI收割
来源：深圳先进技术研究院
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