IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of Object Motion Parameters from Noisy Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optical Flow Estimation: An Error Analysis of Gradient-Based Methods with Local Optimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
3-D motion estimation, understanding, and prediction from nosiy image sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
A simplified linear optic-flow motion algorithm
Computer Vision, Graphics, and Image Processing
Motion and Structure From Two Perspective Views: Algorithms, Error Analysis, and Error Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Some Properties of the E Matrix in Two-View Motion Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Iterated Estimation of the Motion Parameters of a Rigid Body from Noisy Displacement Vectors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matching Two Perspective Views
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iterative solution of nonlinear equations in several variables
Iterative solution of nonlinear equations in several variables
Optimization by Vector Space Methods
Optimization by Vector Space Methods
Detection, Estimation, and Modulation Theory: Radar-Sonar Signal Processing and Gaussian Signals in Noise
Least Square Estimation with Applications to Digital Signal Processing
Least Square Estimation with Applications to Digital Signal Processing
Recursive Estimation of 3D Features Using Optical Flow and Camera Motion
Intelligent Autonomous Systems, An International Conference
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rigidity Checking of 3D Point Correspondences Under Perspective Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Transitory Image Sequences, Asymptotic Properties, and Estimation of Motion and Structure
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Ambiguities in Structure From Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Development and Comparison of Robust Methodsfor Estimating the Fundamental Matrix
International Journal of Computer Vision
Risk-Sensitive Filters for Recursive Estimation of Motion From Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Optimization Criteria Used in Two-View Motion Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reducing "Structure From Motion": A General Framework for Dynamic Vision Part 1: Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometric Information Criterion for Model Selection
International Journal of Computer Vision
A Multi-Frame Structure-from-Motion Algorithm under Perspective Projection
International Journal of Computer Vision - Special issue on computer vision research at NEC Research Institute
Point Light Source Estimation from Two Images and Its Limits
International Journal of Computer Vision
Fast and Globally Convergent Pose Estimation from Video Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal Structure from Motion: Local Ambiguities and Global Estimates
International Journal of Computer Vision
Optimization Criteria and Geometric Algorithms for Motion and Structure Estimation
International Journal of Computer Vision
On the consistency of instantaneous rigid motion estimation
International Journal of Computer Vision
Rigid Body Segmentation and Shape Description from Dense Optical Flow Under Weak Perspective
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recursive Estimation of Motion, Structure, and Focal Length
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optic Flow Field Segmentation and Motion Estimation Using a Robust Genetic Partitioning Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Structure-from-Motion Ambiguity
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structure from Motion Causally Integrated Over Time
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parameter Estimates for a Pencil of Lines: Bounds and Estimators
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
3-D Motion and Structure from 2-D Motion Causally Integrated over Time: Implementation
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Uncertainty Modeling for Optimal Structure from Motion
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Optimization Criteria, Sensitivity and Robustness of Motion and Structure Estimation
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Error Characterization of the Factorization Approach to Shape and Motion Recovery
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
3D Facial Feature Extraction and Global Motion Recovery Using Multi-modal Information
BMVC '00 Proceedings of the First IEEE International Workshop on Biologically Motivated Computer Vision
Registration of technical drawings and calibrated images for industrial augmented reality
Machine Vision and Applications - Special issue: IEEE WACV
Optimal Structure from Motion: Local Ambiguities and Global Estimates
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Stochastic Approximation and Rate-Distortion Analysis for Robust Structure and Motion Estimation
International Journal of Computer Vision
Rank 1 Weighted Factorization for 3D Structure Recovery: Algorithms and Performance Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Linear Motion Estimation for Image Sequence Based Accurate 3-D Measurements
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
The least-squares error for structure from infinitesimal motion
International Journal of Computer Vision
Ego-Motion Estimation and 3D Model Refinement in Scenes with Varying Illumination
WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
An Efficient and Accurate Method for 3D-Point Reconstruction from Multiple Views
International Journal of Computer Vision
Canonical Representation and Multi-View Geometry of Cylinders
International Journal of Computer Vision
Autonomous robot calibration using vision technology
Robotics and Computer-Integrated Manufacturing
Automatic alignment of large-scale aerial rasters to road-maps
Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems
Controlling virtual cameras based on a robust model-free pose acquisition technique
IEEE Transactions on Multimedia
Projective rectification from the fundamental matrix
Image and Vision Computing
Self-calibration of a light striping system by matching multiple 3-D profile maps
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
Dense versus Sparse Approaches for Estimating the Fundamental Matrix
International Journal of Computer Vision
International Journal of Computer Vision
Online computation of exterior orientation with application to hand-eye calibration
Mathematical and Computer Modelling: An International Journal
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The causes of existing linear algorithms exhibiting various high sensitivities to noise are analyzed. It is shown that even a small pixel-level perturbation may override the epipolar information that is essential for the linear algorithms to distinguish different motions. This analysis indicates the need for optimal estimation in the presence of noise. Methods are introduced for optimal motion and structure estimation under two situations of noise distribution: known and unknown. Computationally, the optimal estimation amounts to minimizing a nonlinear function. For the correct convergence of this nonlinear minimization, a two-step approach is used. The first step is using a linear algorithm to give a preliminary estimate for the parameters. The second step is minimizing the optimal objective function starting from that preliminary estimate as an initial guess. A remarkable accuracy improvement has been achieved by this two-step approach over using the linear algorithm alone.