Robust, Real-Time Motion Estimation from Long Image Sequences Using Kalman Filtering

Authors:
J. A. Yang;X. M. Yang
Affiliations:
-;-
Venue:
BMVC '00 Proceedings of the First IEEE International Workshop on Biologically Motivated Computer Vision
Year:
2000

Citing 5
Cited 0

Three-dimensional motion computation and object segmentation in a long sequence of stereo frames

International Journal of Computer Vision
Subspace methods for recovering rigid motion I: algorithm and implementation

International Journal of Computer Vision
Recursive-batch estimation of motion and structure from monocular image sequences

CVGIP: Image Understanding
The Accuracy of the Computation of Optical Flow and of the Recovery of Motion Parameters

IEEE Transactions on Pattern Analysis and Machine Intelligence
3-D Translational Motion and Structure from Binocular Image Flows

IEEE Transactions on Pattern Analysis and Machine Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents how to estimate the left and right monocular motion and structure parameters of two stereo image sequences including direction of translation, relative depth, observer rotation and rotational acceleration, and how to compute absolute depth, absolute translation and absolute translational acceleration parameters at each frame. For improving the accuracy of the computed parameters and robustness of the algorithm, A Kalman filter is used to integrate the parameters over time to provide a "best" estimation of absolute translation at each time.