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Authors: Antti E. Ainasoja ; Antti Hietanen ; Jukka Lankinen and Joni-Kristian Kämäräinen

Affiliation: Tampere University of Technology, Finland

Keyword(s): Video Summarization, Visual Bag-of-Words, Region Descriptors, Optical Flow Descriptors.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Motion, Tracking and Stereo Vision ; Optical Flow and Motion Analyses

Abstract: In this work, we focus on the popular keyframe-based approach for video summarization. Keyframes represent important and diverse content of an input video and a summary is generated by temporally expanding the keyframes to key shots which are merged to a continuous dynamic video summary. In our approach, keyframes are selected from scenes that represent semantically similar content. For scene detection, we propose a simple yet effective dynamic extension of a video Bag-of-Words (BoW) method which provides over segmentation (high recall) for keyframe selection. For keyframe selection, we investigate two effective approaches: local region descriptors (visual content) and optical flow descriptors (motion content). We provide several interesting findings. 1) While scenes (visually similar content) can be effectively detected by region descriptors, optical flow (motion changes) provides better keyframes. 2) However, the suitable parameters of the motion descriptor based keyframe selection vary from one video to another and average performances remain low. To avoid more complex processing, we introduce a human-in-the-loop step where user selects keyframes produced by the three best methods. 3) Our human assisted and learning-free method achieves superior accuracy to learning-based methods and for many videos is on par with average human accuracy. (More)

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Paper citation in several formats:
Ainasoja, A.; Hietanen, A.; Lankinen, J. and Kämäräinen, J. (2018). Keyframe-based Video Summarization with Human in the Loop. In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, ISBN 978-989-758-290-5; ISSN 2184-4321, pages 287-296. DOI: 10.5220/0006619202870296

@conference{visapp18,
author={Antti E. Ainasoja. and Antti Hietanen. and Jukka Lankinen. and Joni{-}Kristian Kämäräinen.},
title={Keyframe-based Video Summarization with Human in the Loop},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,},
year={2018},
pages={287-296},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006619202870296},
isbn={978-989-758-290-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,
TI - Keyframe-based Video Summarization with Human in the Loop
SN - 978-989-758-290-5
IS - 2184-4321
AU - Ainasoja, A.
AU - Hietanen, A.
AU - Lankinen, J.
AU - Kämäräinen, J.
PY - 2018
SP - 287
EP - 296
DO - 10.5220/0006619202870296