Optimal motion parameters and structures estimation of a rigid object from a monocular image sequence

被引：0
|
作者：
Ouyang, GH [1 ]
Sun, JX [1 ]
WAng, XH [1 ]
Li, H [1 ]
Zhong, S [1 ]
机构：
[1] Natl Univ Def Technol, Inst Elect Engn, Changsha 410073, Hunan, Peoples R China
来源：
ULTRAHIGH- AND HIGH-SPEED PHOTOGRAPHY AND IMAGE-BASED MOTION MEASUREMENT | 1997年 / 3173卷
关键词：
3-D object recognition; motion parameters and structures estimation; monocular image sequence; motion model; imaging model; Kalman filtering;
D O I：
10.1117/12.294531
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
In this paper, we propose the optimal estimation of motion parameters and structures of a three-dimensional(3-D) rigid object from a monocular image sequence. First, object motion model and camera imaging model are discussed. And then, through further analysis, the state equation and measurement equation of the object is established, an iterated extended Kalman filtering(IEKF) algorithm is adopted when the estimated system is continuous and nonlinear. The simulative numerical experiments have shown that the presented method is efficient.
引用
收藏
页码：395 / 406
页数：12
相关论文
共 50 条
  • [21] ESTIMATION OF OBJECT MOTION PARAMETERS FROM NOISY IMAGES
    BROIDA, TJ
    CHELLAPPA, R
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1986, 8 (01) : 90 - 99
  • [22] Robust motion estimation for calibrated cameras from monocular image sequences
    Wagner, R
    Liu, FY
    Donner, K
    COMPUTER VISION AND IMAGE UNDERSTANDING, 1999, 73 (02) : 258 - 268
  • [23] Detecting linear motion of an object in a sequence of monocular underwater images
    Lagstad, P
    PROCEEDINGS OF THE 1996 SYMPOSIUM ON AUTONOMOUS UNDERWATER VEHICLE TECHNOLOGY, 1996, : 343 - 347
  • [24] Comparision of Computer Vision and Photogrammetric Approaches for Motion Estimation of Object in an Image Sequence
    Tumurbaatar, Tserennadmid
    Kim, Taejung
    2018 IEEE 3RD INTERNATIONAL CONFERENCE ON IMAGE, VISION AND COMPUTING (ICIVC), 2018, : 581 - 585
  • [25] Motion parameters for unmanned vehicle from an image sequence
    Hassan, H
    White, BA
    UKACC INTERNATIONAL CONFERENCE ON CONTROL '98, VOLS I&II, 1998, : 895 - 900
  • [26] Joint estimation of depth and motion from a monocular endoscopy image sequence using a multi-loss rebalancing network
    Liu, Shiyuan
    Fan, Jingfan
    Song, Dengpan
    Fu, Tianyu
    Lin, Yucong
    Xiao, Deqiang
    Song, Hong
    Wang, Yongtian
    Yang, Jian
    BIOMEDICAL OPTICS EXPRESS, 2022, 13 (05) : 2707 - 2727
  • [27] DIRECT ESTIMATION OF 3-D MOTION PARAMETERS FROM IMAGE SEQUENCE AND DEPTH.
    Yamamoto, Masanobu
    1600, (17):
  • [28] Optimal Estimation of Deterioration From Diagnostic Image Sequence
    Gorinevsky, Dimitry
    Kim, Seung-Jean
    Beard, Shawn
    Boyd, Stephen
    Gordon, Grant
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2009, 57 (03) : 1030 - 1043
  • [29] Robust estimation of 3D trajectories from a monocular image sequence
    Pang, CYC
    Guesalaga, AR
    Roda, VO
    INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, 2002, 12 (03) : 128 - 137
  • [30] ESTIMATION OF OBJECT MOTION PARAMETERS FROM NOISY IMAGES.
    Broida, Ted J.
    Chellappa, Rama
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, PAMI-8 (01) : 90 - 99
12345