Fast Rotation Invariant Object Detection with Gradient based Detection Models

Floris De Smedt, Toon Goedemé

Abstract

Accurate object detection has been studied thoroughly over the years. Although these techniques have become very precise, they lack the capability to cope with a rotated appearance of the object. In this paper we tackle this problem in a two step approach. First we train a specific model for each orientation we want to cover. Next to that we propose the use of a rotation map that contains the predicted orientation information at a specific location based on the dominant orientation. This helps us to reduce the number of models that will be evaluated at each location. Based on 3 datasets, we obtain a high speed-up while still maintaining accurate rotated object detection.

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Paper Citation


in Harvard Style

De Smedt F. and Goedemé T. (2015). Fast Rotation Invariant Object Detection with Gradient based Detection Models . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-090-1, pages 400-407. DOI: 10.5220/0005308404000407


in Bibtex Style

@conference{visapp15,
author={Floris De Smedt and Toon Goedemé},
title={Fast Rotation Invariant Object Detection with Gradient based Detection Models},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={400-407},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005308404000407},
isbn={978-989-758-090-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2015)
TI - Fast Rotation Invariant Object Detection with Gradient based Detection Models
SN - 978-989-758-090-1
AU - De Smedt F.
AU - Goedemé T.
PY - 2015
SP - 400
EP - 407
DO - 10.5220/0005308404000407