Pano2CAD: Room Layout from a Single Panorama Image

Jiu Xu,Björn Stenger,Tommi Kerola,Tony Miu Tung

2017 IEEE Winter Conference on Applications of Computer Vision (WACV)（2017）

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摘要

This paper presents a method of estimating the geometry of a room and the 3D pose of objects from a single 360 panorama image. Assuming ManhattanWorld geometry, we formulate the task as an inference problem in which we estimate positions and orientations of walls and objects. The method combines surface normal estimation, 2D object detection and 3D object pose estimation. Quantitative results are presented on a dataset of synthetically generated 3D rooms containing objects, as well as on a subset of handlabeled images from the public SUN360 dataset.

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关键词

Pano2CAD,room layout,panorama image,room geometry estimation,3D pose estimation,Manhattan World geometry,inference problem,wall orientation estimation,wall position estimation,object position estimation,2D detection,3D object pose estimation,quantitative analysis,synthetically generated 3D rooms,hand-labeled images,public SUN360 dataset,surface normal estimation,object orientation estimation

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