Object Detection Oriented Feature Pooling for Video Semantic Indexing

Kazuya Ueki, Tetsunori Kobayashi

2017

Abstract

We propose a new feature extraction method for video semantic indexing. Conventional methods extract features densely and uniformly across an entire image, whereas the proposed method exploits the object detector to extract features from image windows with high objectness. This feature extraction method focuses on ``objects.'' Therefore, we can eliminate the unnecessary background information, and keep the useful information such as the position, the size, and the aspect ratio of a object. Since these object detection oriented features are complementary to features from entire images, the performance of video semantic indexing can be further improved. Experimental comparisons using large-scale video dataset of the TRECVID benchmark demonstrated that the proposed method substantially improved the performance of video semantic indexing.

Paper Citation

in Harvard Style

Ueki K. and Kobayashi T. (2017). Object Detection Oriented Feature Pooling for Video Semantic Indexing . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-226-4, pages 44-51. DOI: 10.5220/0006099600440051

in Bibtex Style

@conference{visapp17,
author={Kazuya Ueki and Tetsunori Kobayashi},
title={Object Detection Oriented Feature Pooling for Video Semantic Indexing},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={44-51},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006099600440051},
isbn={978-989-758-226-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017)
TI - Object Detection Oriented Feature Pooling for Video Semantic Indexing
SN - 978-989-758-226-4
AU - Ueki K.
AU - Kobayashi T.
PY - 2017
SP - 44
EP - 51
DO - 10.5220/0006099600440051