Estimation of Object Motion Parameters from Noisy Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimating the Kinematics and Structure of a Rigid Object from a Sequence of Monocular Images
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
Transitory Image Sequences, Asymptotic Properties, and Estimation of Motion and Structure
IEEE Transactions on Pattern Analysis and Machine Intelligence
Number of Solutions for Motion and Structure from Multiple FrameCorrespondence
International Journal of Computer Vision
Real-time vision-based camera tracking for augmented reality applications
VRST '97 Proceedings of the ACM symposium on Virtual reality software and technology
Closed Form Solutions for Reconstruction Via Complex Analysis
Journal of Mathematical Imaging and Vision
Vehicle-Type Motion Estimation From Multi-Frame Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Expert: Intelligent Systems and Their Applications
Robust evidence-based object tracking
Pattern Recognition Letters
Complex Analysis for Reconstruction from Controlled Motion
CAIP '99 Proceedings of the 8th International Conference on Computer Analysis of Images and Patterns
A sequential algorithm for motion estimation from point correspondences with intermittent occlusions
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol.2)-Volume 2 - Volume 2
Image processing based tracking system
CIMMACS'06 Proceedings of the 5th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics
Motion of nonrigid objects from multiframe correspondences
Journal of Visual Communication and Image Representation
Identification of a moving object's velocity with a fixed camera
Automatica (Journal of IFAC)
Tracking a Ground Moving Target with a Quadrotor Using Switching Control
Journal of Intelligent and Robotic Systems
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The development of a general motion estimation system based on using three or more frames is reported. The relevant portion of the sequence is treated as a whole, thus simplifying the process of estimating the motion parameters, and making possible the computation of the motion parameters in terms of the natural center of motion. A general description of this motion estimation method is presented, with the derivation of motion equations for three cases (three points in three frames, two points in four frames, and one point in five frames). Results are given for real and synthetic images for the case of one point in five (and six) frames. On the average, the program converged quickly to the right answer for noiseless data. For noisy data, the answers were reasonable and their accuracy was directly a function of the amount of noise in the disparity vector.