A statistical image model for motion estimation

Authors:
Christoph Stiller
Affiliations:
Institute for Communication Engineering, Aachen University of Technology, Aachen, Germany
Venue:
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: image and multidimensional signal processing - Volume V
Year:
1993

Citing 2
Cited 0

An Investigation of Smoothness Constraints for the Estimation of Displacement Vector Fields from Image Sequences

IEEE Transactions on Pattern Analysis and Machine Intelligence
Image segmentation based on object oriented mapping parameter estimation

Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper addresses model based object oriented motion estimation from image sequences. A generic label field segments the scene into several continuously moving 2-D objects. An image model assuming segmentwise stationarity of the displaced frame difference (dfd) and of the estimated fields is proposed. The dfd is shown to obey a white generalized gaussian distribution better than the commonly assumed overall white gaussian distribution. A coupled weak smoothness constraint bounds the segments of the label field to smooth shape and the vector field to smoothness within each of those segments. The MAP-estimator with respect to the image model is derived. Its performance is demonstrated by experimental results.