Optical flow estimation from noisy data using differential techniques

Authors:
Chun-Jen Tsai;N. P. Galatsanos;A. K. Katsaggelos
Affiliations:
Electr. & Comput. Sci., Northwestern Univ., Evanston, IL, USA;-;-
Venue:
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06
Year:
1999

Citing 0
Cited 2

Optical flow using textures

Pattern Recognition Letters
Point Matching under Large Image Deformations and Illumination Changes

IEEE Transactions on Pattern Analysis and Machine Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

Many optical flow estimation techniques are based on the differential optical flow equation. These algorithms involve solving over-determined systems of optical flow equations. Least squares (LS) estimation is usually used to solve these systems even though the underlying noise does not conform to the model implied by LS estimation. To ameliorate this problem, work has been done using the total least squares (TLS) method instead. However, the noise model presumed by TLS is again different from the noise present in the system of optical flow equations. A proper way to solve the system of optical flow equations is the constrained total least squares (CTLS) technique. The derivation and analysis of the CTLS technique for optical flow estimation is presented in this paper. It is shown that CTLS outperforms TLS and LS optical flow estimation.