Orientation Aware Scene Understanding for Mobile Camera

 

Teaser

(Left: Original image with horizon line, detected by camera. Middle: Annotated Ground Truth Image (marked using touch screen), Right: Result of our approach)

In 14th ACM International Conference on Ubiquitous Computing (Ubicomp 2012), Pittsburgh, PA, USA (September 5-8, 2012).

Authors

Jing Wang

Georgia Institute of Technology

Grant Schindler

Georgia Institute of Technology

Irfan Essa

Georgia Institute of Technology

Abstract

We present a novel approach that allows anyone to quickly teach their smartphone how to understand the visual world around them. We achieve this visual scene understanding by leveraging a camera-phone’s inertial sensors to lead to both a faster and more accurate automatic labeling of the regions of an image into semantic classes (e.g. sky, tree, building). We focus on letting a user train our system from scratch while out in the real world by annotating image re- gions in situ as training images are captured on a mobile de- vice, making it possible to recognize new environments and new semantic classes on the fly. We show that our approach outperforms existing methods, while at the same time per- forming data collection, annotation, feature extraction, and image segment classification all on the same mobile device.

Paper

Citation
Jing Wang, Grant Schindler, Irfan Essa (2012), "Orientation Aware Scene Understanding for Mobile Camera", In Proceedings of ACM International Conference on Ubiquitous Computing (Ubicomp), Pittsburgh, PA, Sep 2012.
@inproceedings{Wang:2012:OASUFMC,
       Author = {Jing Wang and Grant Schindler and Essa},
       Booktitle = {Proceedings of ACM International Conference on Ubiquitous Computing (Ubicomp)},
       Month = {September},
       Title = {Orientation Aware Scene Understanding for Mobile Camera},
       Year = {2012},
}
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