Video Highlight Detection via Region-Based Deep Ranking Model

doi:10.1142/S0218001419400019

	Video Highlight Detection via Region-Based Deep Ranking Model
	Jiao, Yifan 1,2; Zhang, Tianzhu2 ; Huang, Shucheng 1; Liu, Bin 3; Xu, Changsheng2
Source Publication	INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
ISSN	0218-0014
	2019-06-30
Volume	33 Issue:7 Pages:14
Corresponding Author	Huang, Shucheng(schuang2015@gmail.com)
Abstract	The video highlight detection task is to localize key elements (moments of user's major or special interest) in a video. Most of the existing highlight detection approaches extract features from the video segment as a whole without considering the difference of local features spatially. In spatial extent, not all regions are worth watching because some of them only contain the background of the environment without human or other moving objects, especially when there is lots of clutter in the background. To deal with this issue, we propose a novel region-based model which can automatically localize the key elements in a video without any extra supervised annotations. Specifically, the proposed model produces position-sensitive score maps for local regions in the spatial dimension of the video segment, and then aggregates all position-wise scores with position-pooling operation. The regions with higher response values will be extracted as key elements. Thus more effective features of the video segment are obtained to predict the highlight score. The proposed position-sensitive scheme can be easily integrated into an endto-end fully convolutional network which aims to update parameters via stochastic gradient descent method in the backward propagation to improve the robustness of the model. Extensive experimental results on the YouTube and SumMe datasets demonstrate that the proposed approach achieves significant improvement over state-of-the-art methods.
Keyword	Video highlight detection position-sensitive fully convolutional network
DOI	10.1142/S0218001419400019
WOS Keyword	SCENE DETECTION
Indexed By	SCI
Language	英语
Funding Project	National Natural Science Foundation of China[61432019] ; National Natural Science Foundation of China[61572498] ; National Natural Science Foundation of China[61532009] ; National Natural Science Foundation of China[61772244] ; Key Research Program of Frontier Sciences, CAS[QYZDJ-SSW-JSC039] ; Beijing Natural Science Foundation[4172062] ; Postgraduate Research & Practice Innovation Program of Jiangsu Province[SJCX17 0599] ; National Natural Science Foundation of China[61432019] ; National Natural Science Foundation of China[61572498] ; National Natural Science Foundation of China[61532009] ; National Natural Science Foundation of China[61772244] ; Key Research Program of Frontier Sciences, CAS[QYZDJ-SSW-JSC039] ; Beijing Natural Science Foundation[4172062] ; Postgraduate Research & Practice Innovation Program of Jiangsu Province[SJCX17 0599]
Funding Organization	National Natural Science Foundation of China ; Key Research Program of Frontier Sciences, CAS ; Beijing Natural Science Foundation ; Postgraduate Research & Practice Innovation Program of Jiangsu Province
WOS Research Area	Computer Science
WOS Subject	Computer Science, Artificial Intelligence
WOS ID	WOS:000470871900001
Publisher	WORLD SCIENTIFIC PUBL CO PTE LTD
Citation statistics	Cited Times:2[WOS] [WOS Record] [Related Records in WOS]
Document Type	期刊论文
Identifier	http://ir.ia.ac.cn/handle/173211/26013
Collection	模式识别国家重点实验室_多媒体计算
Corresponding Author	Huang, Shucheng
Affiliation	1.Jiangsu Univ Sci & Technol, Zhenjiang 212003, Jiangsu, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 3.Moshanghua Tech Co Ltd, Beijing 100030, Peoples R China
First Author Affilication	Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation GB/T 7714	Jiao, Yifan,Zhang, Tianzhu,Huang, Shucheng,et al. Video Highlight Detection via Region-Based Deep Ranking Model[J]. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE,2019,33(7):14.
APA	Jiao, Yifan,Zhang, Tianzhu,Huang, Shucheng,Liu, Bin,&Xu, Changsheng.(2019).Video Highlight Detection via Region-Based Deep Ranking Model.INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE,33(7),14.
MLA	Jiao, Yifan,et al."Video Highlight Detection via Region-Based Deep Ranking Model".INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE 33.7(2019):14.

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