Video object tracking using adaptive Kalman filter

被引:262
作者
Shiuh-Ku Weng
Chung-Ming Kuo
Shu-Kang Tu
机构
[1] Chinese Naval Acad, Dept Informat Management, Kaohsiung 813, Taiwan
[2] I Shou Univ, Dept Informat Engn, Kaohsiung 840, Taiwan
关键词
HSI color space; adaptive Kalman filter; occlusion ratio;
D O I
10.1016/j.jvcir.2006.03.004
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, a new video moving object tracking method is proposed. In initialization, a moving object selected by the user is segmented and the dominant color is extracted from the segmented target. In tracking step, a motion model is constructed to set the system model of adaptive Kalman filter firstly. Then, the dominant color of the moving object in HSI color space will be used as feature to detect the moving object in the consecutive video frames. The detected result is fed back as the measurement of adaptive Kalman filter and the estimate parameters of adaptive Kalman filter are adjusted by occlusion ratio adaptively. The proposed method has the robust ability to track the moving object in the consecutive frames under some kinds of real-world complex situations such as the moving object disappearing totally or partially due to occlusion by other ones, fast moving object, changing lighting, changing the direction and orientation of the moving object, and changing the velocity of moving object suddenly. The proposed method is an efficient video object tracking algorithm. (C) 2006 Elsevier Inc. All rights reserved.
引用
收藏
页码:1190 / 1208
页数:19
相关论文
共 28 条
[1]   Motion segmentation by multistage affine classification [J].
Borshukov, GD ;
Bozdagi, G ;
Altunbasak, Y ;
Tekalp, AM .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 1997, 6 (11) :1591-1594
[2]   Efficient moving object segmentation algorithm using background registration technique [J].
Chien, SY ;
Ma, SY ;
Chen, LG .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2002, 12 (07) :577-586
[3]  
FABER V, 1994, LOS ALAMOS SCI, P138
[4]  
Gonzalez R., 2019, Digital Image Processing, V2nd
[5]   2D human body tracking with Structural Kalman filter [J].
Jang, DS ;
Jang, SW ;
Choi, HI .
PATTERN RECOGNITION, 2002, 35 (10) :2041-2049
[6]   Active models for tracking moving objects [J].
Jang, DS ;
Choi, HI .
PATTERN RECOGNITION, 2000, 33 (07) :1135-1146
[7]  
Jepson A.D., 2001, P COMP VIS PATT REC
[8]  
JOHNSON I, 1999, REAL-TIME IMAGING, P295
[9]   Fast and automatic video object segmentation and tracking for content-based applications [J].
Kim, C ;
Hwang, JN .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2002, 12 (02) :122-129
[10]  
Kim Jong Bae, REAL TIME REGION BAS