Evaluation of shadow features

doi:10.1049/iet-cvi.2017.0159

CORC > 金属研究所 > 中国科学院金属研究所

	Evaluation of shadow features
	Qu, Liangqiong 1,2,3; Tian, Jiandong 2; Fan, Huijie 2; Li, Wentao 2; Tang, Yandong 2
刊名	IET COMPUTER VISION
	2018-02-01
卷号	12 期号:1 页码:95-103
关键词	object detection image texture image colour analysis image classification shadow features colour ratio chromaticity shadow detection methods
ISSN号	1751-9632
DOI	10.1049/iet-cvi.2017.0159
通讯作者	Tian, Jiandong(tianjd@sia.cn)
英文摘要	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.
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
语种	英语
出版者	INST ENGINEERING TECHNOLOGY-IET
WOS记录号	WOS:000423200200011
资助机构	Natural Science Foundation of China ; Youth Innovation Promotion Association CAS
内容类型	期刊论文
源URL	[http://ir.imr.ac.cn/handle/321006/127225]
专题	金属研究所_中国科学院金属研究所
通讯作者	Tian, Jiandong
作者单位	1.Univ Chinese Acad Sci, Beijing, Peoples R China 2.Chinese Acad Sci, Shenyang Inst Automat, State Key Lab Robot, Shenyang, Liaoning, 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.