Share Email Print
cover

Proceedings Paper

Parallel genetic search algorithm for motion estimation
Author(s): Savio Lai Yin Lam; Ishfaq Ahmad
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Motion estimation is perhaps the most computationally intensive aspect of video compression. There are two major approaches to motion estimation: pel recursive and block matching. In the former approach, estimation of motion vectors is done recursively such that the motion compensated prediction error at each pel instant is minimized. In the latter approach, motion estimation is carried out on a block-by-block basis. Comparing with the pel recursive algorithms, the block matching algorithms are more realizable due to their computational simplicity. In this paper, we present a parallel algorithm using genetic search for block-based motion. The first objective of the proposed approach is to remove the need for exhaustive search by making use of genetic algorithms (GA). The second objective is to run this algorithm in parallel so that the computing time is further reduced. The algorithm is implemented using the Express library for a network of workstations and NX for the Intel Paragon.

Paper Details

Date Published: 19 January 1996
PDF: 11 pages
Proc. SPIE 2617, Multimedia: Full-Service Impact on Business, Education, and the Home, (19 January 1996); doi: 10.1117/12.230425
Show Author Affiliations
Savio Lai Yin Lam, Hong Kong Univ. of Science and Technology (Hong Kong)
Ishfaq Ahmad, Hong Kong Univ. of Science and Technology (Hong Kong)


Published in SPIE Proceedings Vol. 2617:
Multimedia: Full-Service Impact on Business, Education, and the Home
Yuet C. Lee; Shekar Rao; Arif Ghafoor, Editor(s)

© SPIE. Terms of Use
Back to Top