A number of methods have been proposed in the literature for estimating scenestructure and ego-motion from a sequence of images using dynamical models. Despite the fact that all methods may be derived from a "natural " dynamical model within a unified framework, from an engineering perspective there are a number of trade-offs that lead to different strategies depending upon the applications and the goals one is targeting. We want to characterize and compare the properties of each model such that the engineer may choose the one best suited to the specific application. We analyze the properties of filters derived from each dynamical model under a variety of experimental conditions, assess the accuracy of the estimates, their robustness to measurement noise, sensitivity to initial conditions and visual angle, effects of the bas-relief ambiguity and occlusions, dependence upon the number of image measurements and their sampling rate. 1
|
1143
|
Matrix Computations
– Golub, Loan
- 1989
|
|
964
|
An iterative image registration technique with an application to stereo vision
– Lucas, Kanade
- 1981
|
|
686
|
Performance of optical flow techniques
– Barron, Fleet, et al.
- 1994
|
|
639
|
Shape and motion from image streams under ortography: a factorization approach
– Tomasi, Kanade
- 1992
|
|
482
|
A computer algorithm for reconstructing a scene from two projections," Nature 293
– Longuet-Higgins
|
|
369
|
A Mathematical Introduction to Robotic Manipulation
– Murray, Li, et al.
- 1994
|
|
351
|
Stochastic Processes and Filtering Theory
– Jazwinski
- 1970
|
|
330
|
Nonlinear Control Systems
– Isidori
- 1995
|
|
211
|
Determining three-dimensional motion and structure from optical flow generated by several moving objects
– Adiv
- 1985
|
|
207
|
An Introduction to Differentiable Manifolds and Riemannian
– Boothby
- 1986
|
|
199
|
A paraperspective factorization method for shape and motion recovery
– Poelman, Kanade
- 1997
|
|
198
|
Recursive estimation of motion, structure, and focal length
– Azarbayejani, Pentland
- 1995
|
|
169
|
Recovering 3D shape and motion from image streams using non linear least squares
– Fua, Szeliski, et al.
- 1994
|
|
163
|
Kalman filterbased algorithms for estimating depth from image sequences
– Matthies, Kanade, et al.
- 1989
|
|
154
|
Algebraic projective geometry
– Semple, Kneebone
- 1952
|
|
148
|
Theory of Reconstruction from Image Motion
– Maybank
- 1993
|
|
122
|
Optimal motion and structure estimation
– Weng, Ahuja, et al.
- 1993
|
|
112
|
Subspace methods for recovering rigid motion i: algorithm and implementation
– Jepson, Heeger
- 1992
|
|
99
|
Differential Topology
– Guillemin, Pollack
- 1974
|
|
87
|
Estimation of Object Motion Parameters from Noisy Images
– Broida, Chellapa
- 1985
|
|
73
|
Applications of dynamic monocular machine vision
– Dickmanns, Graefe
- 1988
|
|
72
|
Recursive 3-D motion estimation from a monocular sequence
– Broida, Chandrashekhar, et al.
- 1990
|
|
71
|
Estimating the Kinematics and Structure of a Rigid Object from a Sequence of Monocular Images
– Broida, Chellappa
- 1991
|
|
51
|
Representation of scenes from collections of images
– Kumar, Anandan, et al.
- 1995
|
|
46
|
Shape recovery from multiple views: a parallax based approach
– Kumar, Anandan, et al.
- 1994
|
|
44
|
Motion estimation via dynamic vision
– Soatto, Frezza, et al.
- 1996
|
|
42
|
Simplifying motion and structure analysis using planar parallax and image warping
– Sawhney
- 1994
|
|
40
|
Comparison of approaches to egomotion computation
– Tian, Tomasi, et al.
- 1996
|
|
39
|
Recursive affine structure and motion from image sequences
– McLauchlan, Reid, et al.
- 1994
|
|
37
|
Multi-frame approach to visual motion perception
– Spetsakis, Aloimonos
- 1991
|
|
37
|
Three dimensional vision, a geometric viewpoint
– Faugeras
- 1993
|
|
28
|
Direct estimation of structure and motion from multiple frames
– Heel
- 1990
|
|
26
|
Recursive motion and structure estimation with complete error characterization
– Frezza, Soatto, et al.
- 1993
|
|
24
|
Direct recovery of motion and shape in the general case by xation
– Taalebinezhaad
- 1992
|
|
23
|
Subspace methods for recovering rigid motion
– Heeger, Jepson
- 1992
|
|
22
|
Recursive Multi-frame Structure from Motion Incorporating Motion Error
– Thomas, Oliensis
- 1992
|
|
19
|
Tracking facilitates 3-D motion estimation
– Fermuller, Aloimonos
- 1992
|
|
17
|
Tracking known 3-dimensional object
– Gennery
- 1982
|
|
17
|
Relative orientation. Int
– Horn
- 1990
|
|
14
|
Recursive 3-d visual motion estimation using subspace constraints
– Soatto, Perona
- 1997
|
|
12
|
Observability/identifiability of rigid motion under perspective projection
– Soatto
- 1994
|
|
12
|
Three dimensional transparent structure segmentation and multiple 3D motion estimation from monocular perspective image sequences
– Soatto, Perona
- 1994
|
|
11
|
Recursive-batch estimation of motion and structure from monocular image sequences
– Cui, Weng, et al.
- 1994
|
|
11
|
Linear structure from motion
– Thomas, Simoncelli
- 1994
|
|
9
|
Motion and structure from point correspondences with error estimation: Planar surfaces
– Weng, Huang, et al.
- 1991
|
|
8
|
A unified approach to camera fixation and vision-based road following
– Raviv, Herman
- 1994
|
|
5
|
3-d structure from visual motion: modeling, representation and observability
– Soatto
- 1997
|
|
4
|
Structure from visual motion as a nonlinear observation problem
– Soatto, Frezza, et al.
- 1995
|
|
4
|
Motion from fixation
– Soatto, Perona
- 1995
|
|
2
|
Linear Fitting with Missing Data
– Jacobs
- 1997
|
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