Binocular Image Flows: Steps Toward Stereo-Motion Fusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of Object Motion Parameters from Noisy Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion and time-varying imagery
Proc. of the ACM SIGGRAPH/SIGART interdisciplinary workshop on Motion: representation and perception
Finding Trajectories of Feature Points in a Monocular Image Sequence
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
Error Analysis in Stereo Determination of 3-D Point Positions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robot Vision
Linear System Theory and Design
Linear System Theory and Design
Estimating the Kinematics and Structure of a Rigid Object from a Sequence of Monocular Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Analysis of Inherent Ambiguities in Recovering 3-D Motion from a Noisy Flow Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of Displacements from Two 3-D Frames Obtained From Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recursive 3-D Visual Motion Estimation Using Subspace Constraints
International Journal of Computer Vision
A General Motion Model and Spatio-Temporal Filters forComputing Optical Flow
International Journal of Computer Vision
A model-based 3-D tracking of rigid objects from a sequence of multiple perspective views
Pattern Recognition Letters
Practical Structure and Motion from Stereo When Motion is Unconstrained
International Journal of Computer Vision
Tracking Nonrigid Motion and Structure from 2D Satellite Cloud Images without Correspondences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unbiased Estimation and Statistical Analysis of 3-D Rigid Motion from Two Views
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust 3-D-3-D Pose Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recursive Estimation of Motion, Structure, and Focal Length
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Structure-from-Motion Ambiguity
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stochastic Approximation and Rate-Distortion Analysis for Robust Structure and Motion Estimation
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Multi-Scale 3D Scene Flow from Binocular Stereo Sequences
WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
Global motion model for stereovision-based motion analysis
EURASIP Journal on Applied Signal Processing
Multi-scale 3D scene flow from binocular stereo sequences
Computer Vision and Image Understanding
Image and Vision Computing
An integrated stereo visual odometry for robotic navigation
Robotics and Autonomous Systems
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A kinematic model-based approach for the estimation of 3-D motion parameters from a sequence of noisy stereo images is discussed. The approach is based on representing the constant acceleration translational motion and constant precession rotational motion in the form of a bilinear state-space model using standard rectilinear states for translation and quaternions for rotation. Closed-form solutions of the state transition equations are obtained to propagate the quaternions. The measurements are noisy perturbations of 3-D feature points represented in an inertial coordinate system. It is assumed that the 3-D feature points are extracted from the stereo images and matched over the frames. Owing to the nonlinearity in the state model, nonlinear filters are designed for the estimation of motion parameters. Simulation results are included. The Cramer-Rao performance bounds for motion parameter estimates are computed. A constructive proof for the uniqueness of motion parameters is given. It is shown that with uniform sampling in time, three noncollinear feature points in five consecutive binocular image pairs contain all the spatial and temporal information. Both nondegenerate and degenerate motions are analyzed. A deterministic algorithm to recover motion parameters from a stereo image sequence is summarized from the constructive proof.