图 书 馆
3D模型中的数据驱动场景理解Data-Driven Scene Understanding from 3D Models |
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| 课程网址: | http://videolectures.net/bmvc2012_satkin_scene_understanding/ |
| 主讲教师: | Scott Satkin |
| 开课单位: | 卡内基梅隆大学 |
| 开课时间: | 2012-10-09 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In this paper, we propose a data-driven approach to leverage repositories of 3D models for scene understanding. Our ability to relate what we see in an image to a large collection of 3D models allows us to transfer information from these models, creating a rich understanding of the scene. We develop a framework for auto-calibrating a camera, rendering 3D models from the viewpoint an image was taken, and computing a similarity measure between each 3D model and an input image. We demonstrate this data-driven approach in the context of geometry estimation and show the ability to find the identities and poses of object in a scene. Additionally, we present a new dataset with annotated scene geometry. This data allows us to measure the performance of our algorithm in 3D, rather than in the image plane. |
| 关 键 词: | 数据驱动方法; 3D模型; 自动校准相机 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-09-24：dingaq |
| 阅读次数: | 139 |