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基于RGBD图像推断支持实现室内对象分割Indoor Segmentation and Support Inference from RGBD Images |
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| 课程网址: | http://videolectures.net/eccv2012_silberman_images/ |
| 主讲教师: | Silvio Savarese, Nathan Silberman, Aude Oliva |
| 开课单位: | 纽约大学 |
| 开课时间: | 2012-11-12 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We present an approach to interpret the major surfaces, objects, and support relations of an indoor scene from an RGBD image. Most existing work ignores physical interactions or is applied only to tidy rooms and hallways. Our goal is to parse typical, often messy, indoor scenes into floor, walls, supporting surfaces, and object regions, and to recover support relationships. One of our main interests is to better understand how 3D cues can best inform a structured 3D interpretation. We also contribute a novel integer programming formulation to infer physical support relations. We offer a new dataset of 1449 RGBD images, capturing 464 diverse indoor scenes, with detailed annotations. Our experiments demonstrate our ability to infer support relations in complex scenes and verify that our 3D scene cues and inferred support lead to better object segmentation. |
| 关 键 词: | 3D线索; RGBD图像; 室内场景 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-03-23：lxf |
| 阅读次数: | 162 |