IMAGE DESCRIPTION AND 3-D RECONSTRUCTION FROM IMAGE TRAJECTORIES OF ROTATIONAL MOTION

被引:9
|
作者
SAWHNEY, HS
OLIENSIS, J
HANSON, AR
机构
[1] UNIV MASSACHUSETTS,DEPT COMP & INFORMAT SCI,AMHERST,MA 01003
[2] UNIV MASSACHUSETTS,COMP VIS LAB,AMHERST,MA 01003
基金
美国国家科学基金会;
关键词
CONIC CURVE FITTING; IMAGE SEQUENCE ANALYSIS; MOTION TRAJECTORIES; NONLINEAR OPTIMIZATION; SPATIAL AND TEMPORAL GROUPING; STRUCTURE FROM MOTION; TIME-VARYING IMAGERY;
D O I
10.1109/34.232075
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a new technique for reconstructing the 3-D structure and motion of a scene undergoing relative rotational motion with respect to the camera. Given image correspondences of point features tracked over many frames, a two-stage technique for reconstruction is presented. First, a grouping algorithm that exploits spatio-temporal constraints of the common motion to achieve a reliable description of discrete point correspondences as curved trajectories (general conics in the case of rotational motion) in the image plane is developed. In contrast, trajectories fitted to points independent of each other lead to arbitrary image descriptions and very inaccurate 3-D parameters. Second, a new closed-form solution, under perspective projection, for the 3-D motion and location of points from the computed image trajectories is presented. Both stages are applied to real image sequences with good results. This approach represents a first step in a longer-term research effort examining the role of explicit spatio-temporal organization in the interpretation of scenes from dynamic images.
引用
收藏
页码:885 / 898
页数:14
相关论文
共 50 条
  • [41] An Image Reconstruction Algorithm for 3-D Electrical Impedance Mammography
    Zhang, Xiaolin
    Wang, Wei
    Sze, Gerald
    Barber, David
    Chatwin, Chris
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2014, 33 (12) : 2223 - 2241
  • [42] Motion image segmentation using 3-D watershed algorithm
    Yoshida, T
    Shimosato, T
    2001 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL II, PROCEEDINGS, 2001, : 773 - 776
  • [43] USE OF A TRANSPUTER SYSTEM FOR FAST 3-D IMAGE-RECONSTRUCTION IN 3-D PET
    BARRESI, S
    BOLLINI, D
    DELGUERRA, A
    IEEE TRANSACTIONS ON NUCLEAR SCIENCE, 1990, 37 (02) : 812 - 816
  • [44] 3-D Tomosynthesis Image Reconstruction Using Total Variation
    Ertas, Metin
    Akan, Aydin
    Cengiz, Kubra
    Kamasak, Mustafa
    Seyyedi, Saeed
    Yildirim, Isa
    2012 ASE INTERNATIONAL CONFERENCE ON BIOMEDICAL COMPUTING (BIOMEDCOM), 2012, : 1 - 5
  • [45] The study of 3-D surface reconstruction in digital image processing
    Qu, Zhong
    Nonlinear Science and Complexity, 2007, 1 : 531 - 536
  • [46] FROM ESCARGOT TO 3-D IMAGE GUIDANCE
    Ash, D.
    RADIOTHERAPY AND ONCOLOGY, 2010, 96 : S131 - S131
  • [47] RaNeRF: Neural 3-D Reconstruction of Space Targets From ISAR Image Sequences
    Liu, Afei
    Zhang, Shuanghui
    Zhang, Chi
    Zhi, Shuaifeng
    Li, Xiang
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 61
  • [48] DESCRIPTION OF AN OPTICAL HOLOGRAPHIC SYSTEM FOR 3-D RADIOGRAPHIC IMAGE DISPLAY
    ELLINGSON, WA
    TRANSACTIONS OF THE AMERICAN NUCLEAR SOCIETY, 1975, 21 (JUN): : 100 - 101
  • [49] Estimating 3-D respiratory motion from orbiting views by tomographic image registration
    Zeng, Rongping
    Fessler, Jeffrey A.
    Balter, James M.
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2007, 26 (02) : 153 - 163
  • [50] DIRECT ESTIMATION OF 3-D MOTION PARAMETERS FROM IMAGE SEQUENCE AND DEPTH.
    Yamamoto, Masanobu
    1600, (17):