Conference icon

Conference

Learning texton models for real-time scene context

Abstract:
We present a new model for scene context based on the distribution of textons within images. Our approach provides continuous, consistent scene gist throughout a video sequence and is suitable for applications in which the camera regularly views uninformative parts of the scene. We show that our model outperforms the state-of-the-art for place recognition. We further show how to deduce the camera orientation from our scene gist and finally show how our system can be applied to active object search. © 2009 IEEE.
Publication status:
Published

Actions


Access Document


Publisher copy:
10.1109/CVPR.2009.5204356

Authors


Pages:
41-48
Publication date:
2009
DOI:
ISSN:
1063-6919
URN:
uuid:cbb62d76-f1ac-424e-99a2-7fcf641d0f03
Source identifiers:
108930
Local pid:
pubs:108930
ISBN:
978-1-4244-3994-2

Terms of use


Metrics



If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP