New trends on moving object detection in video images captured by a moving camera: A survey

被引:143
作者
Yazdi, Mehran [1 ,2 ]
Bouwmans, Thierry [2 ]
机构
[1] Shiraz Univ, Lab Signal & Image Proc, Fac Elect & Comp Engn, Shiraz, Iran
[2] Univ La Rochelle, Lab MIA, La Rochelle, France
关键词
Moving object detection; Moving camera; Background subtraction; Motion compensation; REAL-TIME TRACKING; BACKGROUND SUBTRACTION; VISUAL SURVEILLANCE; MOTION DETECTION; PERFORMANCE EVALUATION; MULTITARGET TRACKING; APPEARANCE MODELS; SHADOW DETECTION; PARTICLE FILTER; ROBUST;
D O I
10.1016/j.cosrev.2018.03.001
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a survey on the latest methods of moving object detection in video sequences captured by a moving camera. Although many researches and excellent works have reviewed the methods of object detection and background subtraction for a fixed camera, there is no survey which presents a complete review of the existing different methods in the case of moving camera. Most methods in this field can be classified into four categories; modeling based background subtraction, trajectory classification, low rank and sparse matrix decomposition, and object tracking. We discuss in details each category and present the main methods which proposed improvements in the general concept of the techniques. Wealso present challenges and main concerns in this field as well as performance metrics and some benchmark databases available to evaluate the performance of different moving object detection algorithms. (C) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码:157 / 177
页数:21
相关论文
共 208 条
[61]  
Brox T, 2010, LECT NOTES COMPUT SC, V6315, P282, DOI 10.1007/978-3-642-15555-0_21
[62]   Robust Principal Component Analysis? [J].
Candes, Emmanuel J. ;
Li, Xiaodong ;
Ma, Yi ;
Wright, John .
JOURNAL OF THE ACM, 2011, 58 (03)
[63]  
Chauhan A. K., 2013, INT J ADV RES COMPUT, V3, P243
[64]   Robust salient motion detection in non-stationary videos via novel integrated strategies of spatio-temporal coherency clues and low-rank analysis [J].
Chen, Chenglizhao ;
Li, Shuai ;
Qin, Hong ;
Hao, Aimin .
PATTERN RECOGNITION, 2016, 52 :410-432
[65]   PLS-CCA heterogeneous features fusion-based low-resolution human detection method for outdoor video surveillance [J].
Chen H.-K. ;
Zhao X.-G. ;
Sun S.-Y. ;
Tan M. .
International Journal of Automation and Computing, 2017, 14 (02) :136-146
[66]   Enhancing Detection Model for Multiple Hypothesis Tracking [J].
Chen, Jiahui ;
Sheng, Hao ;
Zhang, Yang ;
Xiong, Zhang .
2017 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW), 2017, :2143-2152
[67]   Real-Time Object Tracking on a Drone With Multi-Inertial Sensing Data [J].
Chen, Peng ;
Dang, Yuanjie ;
Liang, Ronghua ;
Zhu, Wei ;
He, Xiaofei .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2018, 19 (01) :131-139
[68]   Object-Level Motion Detection From Moving Cameras [J].
Chen, Tao ;
Lu, Shijian .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2017, 27 (11) :2333-2343
[69]  
Chetverikov D, 2005, ADV SOFT COMP, P17
[70]   A real-time object tracking system using a particle filter [J].
Cho, Jung Uk ;
Jin, Seung Hun ;
Pham, Xuan Dai ;
Jeon, Jae Wook ;
Byun, Jong Eun ;
Kang, Hoon .
2006 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-12, 2006, :2822-2827