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Authors: Hatem Belhassen 1 ; Heng Zhang 2 ; Virginie Fresse 3 and El-Bay Bourennane 4

Affiliations: 1 Beamtek SAS, 145 Rue Gustave Eiffel, 69330 Meyzieu, France, Hubert Curien Laboratory, Jean Monnet University, Saint Etienne, France, Univ of Burgundy - Franche-Comte, LE2I laboratory, France ; 2 Beamtek SAS, 145 Rue Gustave Eiffel, 69330 Meyzieu, France ; 3 Hubert Curien Laboratory, Jean Monnet University, Saint Etienne, France ; 4 Univ of Burgundy - Franche-Comte, LE2I laboratory, France

ISBN: 978-989-758-354-4

Keyword(s): Video Understanding, Real-time Video Object Detection, Online Object Detection.

Abstract: Video object detection has drawn more and more attention in recent years. Compared with object detection from image, object detection in video is more useful in many practical applications, e.g. self-driving cars, smart video surveillance, etc. It is highly required to build a fast, reliable and low-cost video-based object detection system for these applications. In this work, we propose a novel, simple and highly effective box-level post-processing method to improve the accuracy of video object detection. The proposed method is based on both online and an offline settings. Our experiments on ImageNet object detection from video (VID) dataset show that our method brings important accuracy gains, especially to more challenging fast-moving object detection, with quite light computational overhead in both settings. Applied to YOLOv3, our system achieves so far the best speed/accuracy trade-off for offline video object detection and competitive detection improvements for online object det ection. (More)

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Paper citation in several formats:
Belhassen, H.; Zhang, H.; Fresse, V. and Bourennane, E. (2019). Improving Video Object Detection by Seq-Bbox Matching.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-354-4, pages 226-233. DOI: 10.5220/0007260002260233

@conference{visapp19,
author={Hatem Belhassen. and Heng Zhang. and Virginie Fresse. and El{-}Bay Bourennane.},
title={Improving Video Object Detection by Seq-Bbox Matching},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2019},
pages={226-233},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007260002260233},
isbn={978-989-758-354-4},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,
TI - Improving Video Object Detection by Seq-Bbox Matching
SN - 978-989-758-354-4
AU - Belhassen, H.
AU - Zhang, H.
AU - Fresse, V.
AU - Bourennane, E.
PY - 2019
SP - 226
EP - 233
DO - 10.5220/0007260002260233

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