Scheduled System Maintenance on May 29th, 2015:
IEEE Xplore will be upgraded between 11:00 AM and 10:00 PM EDT. During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

An 8×8-block based motion estimation using Kalman filter

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Ruiz, V. ; Electron. Lab., Patras Univ., Greece ; Fotopoulos, V. ; Skodras, A.N. ; Constantinides, A.G.

It is now quite common in the pel-recursive approaches for motion estimation, to find applications of the Kalman filtering technique both in time and frequency domains. In the block-based approach, very few approaches are available of this technique to refine the estimation of motion vectors resulting from fast algorithms such as the three step on a 16×16-block basis. This paper proposes an 8×8-block based motion estimation which uses the Kalman filtering technique to improve the motion estimates resulting from both the three step algorithm and the previous 16×16-block based Kalman application of Kuo et al. (1996). The state-space representation uses a first order auto-regressive model. Comparative results obtained for different classes of video sequences are presented

Published in:

Image Processing, 1997. Proceedings., International Conference on  (Volume:2 )

Date of Conference:

26-29 Oct 1997