A Kalman filter in motion analysis from stereo image sequences

J. N. Pan, Y. Q. Shi, C. Q. Shu

Research output: Contribution to journalConference articlepeer-review

8 Scopus citations

Abstract

In this paper, a Kalman filter-based algorithm for 3-D motion estimation from a stereo image sequence using the unified temporal-spatial optical flow field (UOFF) has been proposed. The modeling problem is discussed first. More consideration has been given to determining the covariance matrices for system noise and sensor noise than the previous works using Kalman filtering in image sequence processing. The newly visible image areas, i.e., the disocclusion issue, which have not been considered in the most of previous works, are handled in our algorithm by using a threshold method. Two experiments are presented to demonstrate the effectiveness of our algorithm.

Original languageEnglish (US)
Article number413887
Pages (from-to)63-67
Number of pages5
JournalProceedings - International Conference on Image Processing, ICIP
Volume3
DOIs
StatePublished - Jan 1 1994
EventProceedings of the 1994 1st IEEE International Conference on Image Processing. Part 3 (of 3) - Austin, TX, USA
Duration: Nov 13 1994Nov 16 1994

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Fingerprint Dive into the research topics of 'A Kalman filter in motion analysis from stereo image sequences'. Together they form a unique fingerprint.

Cite this