Evaluation of shadow features
文献类型：期刊论文
| 作者 | Qu, Liangqiong1,2,3; Tian, Jiandong1; Fan, Huijie1; Li, Wentao1; Tang, Yandong1 |
| 刊名 | IET COMPUTER VISION
 |
| 出版日期 | 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 |
| WOS记录号 | WOS:000423200200011 |
| 出版者 | INST ENGINEERING TECHNOLOGY-IET |
| 资助机构 | Natural Science Foundation of China ; Youth Innovation Promotion Association CAS |
| 源URL | [http://ir.imr.ac.cn/handle/321006/127221]  |
| 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.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. |
入库方式： OAI收割
来源：金属研究所
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