Understanding Indoor Scenes using 3D Geometric Phrases
Venue
Proceedings of International Conference on Computer Vision and Pattern Recognition (CVPR 2013)
Publication Year
2013
Authors
Wongun Choi, Yu-Wei Chao, Caroline Pantofaru, Silvio Savarese
BibTeX
Abstract
Visual scene understanding is a difficult problem interleaving object detection,
geometric reasoning and scene classification. We present a hierarchical scene model
for learning and reasoning about complex indoor scenes which is computationally
tractable, can be learned from a reasonable amount of training data, and avoids
oversimplification. At the core of this approach is the 3D Geometric Phrase Model
which captures the semantic and geometric relationships between objects which
frequently co-occur in the same 3D spatial configuration. Experiments show that
this model effectively explains scene semantics, geometry and object groupings from
a single image, while also improving individual object detections.
