Evaluation of shadow features

doi:10.1049/iet-cvi.2017.0159

IMR OpenIR

	Evaluation of shadow features
	Qu, Liangqiong 1,2,3; Tian, Jiandong 1; Fan, Huijie 1; Li, Wentao 1; Tang, Yandong 1
通讯作者	Tian, Jiandong(tianjd@sia.cn)
	2018-02-01
发表期刊	IET COMPUTER VISION
ISSN	1751-9632
卷号	12 期号:1 页码:95-103
摘要	Shadow features such as colour ratio, texture, and chromaticity have proved to be quite effective in shadow detection. Many shadow detection methods have been proposed on the basis of different features. However, previous works for shadow detection mainly focus on designing an effective classifier for existing shadow features, but pay less attention on the analysis of shadow features themselves. The majority of studies simply report the final shadow detection results rather than make an evaluation on each feature. Readers often do not know which features are more effective or whether these shadow features are complementary. The following problems are still unsolved: the robustness of each feature, which feature plays the most important role in a detection method, and what is the best performance that current features can reach. The purpose of this study is to answer these questions, and the authors hope that this study can offer guidance for future shadow detection algorithms via the evaluation of frequently used shadow features. Several useful and interesting conclusions are obtained after conducting extensive comparison experiments on a large dataset.
关键词	object detection image texture image colour analysis image classification shadow features colour ratio chromaticity shadow detection methods
资助者	Natural Science Foundation of China ; Youth Innovation Promotion Association CAS
DOI	10.1049/iet-cvi.2017.0159
收录类别	SCI
语种	英语
资助项目	Natural Science Foundation of China[61473280] ; Natural Science Foundation of China[61333019] ; Natural Science Foundation of China[91648118] ; Youth Innovation Promotion Association CAS
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000423200200011
出版者	INST ENGINEERING TECHNOLOGY-IET
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/127222
专题	中国科学院金属研究所
通讯作者	Tian, Jiandong
作者单位	1.Chinese Acad Sci, Shenyang Inst Automat, State Key Lab Robot, Shenyang, Liaoning, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.City Univ Hong Kong, Dept Comp Sci, Kowloon, Hong Kong, Peoples R China
推荐引用方式 GB/T 7714	Qu, Liangqiong,Tian, Jiandong,Fan, Huijie,et al. Evaluation of shadow features[J]. IET COMPUTER VISION,2018,12(1):95-103.
APA	Qu, Liangqiong,Tian, Jiandong,Fan, Huijie,Li, Wentao,&Tang, Yandong.(2018).Evaluation of shadow features.IET COMPUTER VISION,12(1),95-103.
MLA	Qu, Liangqiong,et al."Evaluation of shadow features".IET COMPUTER VISION 12.1(2018):95-103.