A survey of variational and CNN-based optical flow techniques

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成果类型：

期刊论文

作者：

Tu, Zhigang*;Xie, Wei*（谢伟）;Zhang, Dejun;Poppe, Ronald;Veltkamp, Remco C.;...

通讯作者：

Tu, Zhigang;Xie, Wei

作者机构：

[Tu, Zhigang] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Hubei, Peoples R China.

[Xie, Wei] Cent China Normal Univ, Sch Comp, LuoyuRd 152, Wuhan, Hubei, Peoples R China.

[Zhang, Dejun] China Univ Geosci, Sch Informat Engn, Wuhan 30074, Hubei, Peoples R China.

[Poppe, Ronald; Veltkamp, Remco C.] Univ Utrecht, Dept Informat & Comp Sci, Princetonpl 5, Utrecht, Netherlands.

[Li, Baoxin] Arizona State Univ, Sch Comp, Informat, Decis Syst Engn, Tempe, AZ 85287 USA.

通讯机构：

[Tu, Zhigang] W

[Xie, Wei] C

Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Hubei, Peoples R China.

Cent China Normal Univ, Sch Comp, LuoyuRd 152, Wuhan, Hubei, Peoples R China.

语种：

英文

关键词：

Optical flow;Variational method;CNN-based method;Evaluation measures;Challenges

期刊：

Signal Processing: Image Communication

ISSN：

0923-5965

年：

2019

卷：

页码：

9-24

DOI：

10.1016/j.image.2018.12.002

基金类别：

Wuhan University [CXFW-18-413100063]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61501198]; Natural Science Foundation of Hubei Province, ChinaNatural Science Foundation of Hubei Province [2014CFB461, 2017CFB598]

机构署名：

本校为通讯机构

院系归属：

计算机学院

摘要：

Dense motion estimations obtained from optical flow techniques play a significant role in many image processing and computer vision tasks. Remarkable progress has been made in both theory and its application in practice. In this paper, we provide a systematic review of recent optical flow techniques with a focus on the variational method and approaches based on Convolutional Neural Networks (CNNs). These two categories have led to state-of-the-art performance. We discuss recent modifications and extensions of the original model, and highlight remaining challenges. For the first time, we provid...

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A survey of variational and CNN-based optical flow techniques

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