An integrated dynamic scene algorithm for segmentation and motion estimation

Ikhlas Abdel-Qader, Tomislav Bujanovic

Research output: Contribution to journalArticle

Abstract

Segmentation and motion estimation are two problems that require accurate estimation for many applications in computer vision and image analysis. This work presents a solution to these two problems simultaneously. Both the segmentation and motion fields are integrated and estimated in parallel to reduce computation time. The presented algorithm is based on producing motion estimates and restored pixel intensity values through an optimization process that uses deterministic mean-field annealing (MFA) framework. The MFA results at different temperature values are used to run a segmentation process using the concept of region-growing-based algorithm. The segmentation process starts at high temperatures and continues in parallel to the annealing process to refine the segmentation process at lower temperatures. The algorithm results are good and dependent on the annealing parameters. Several experimental results from synthetic and real-world sequences are presented.

Original languageEnglish (US)
Pages (from-to)1845-1853
Number of pages9
JournalEurasip Journal on Applied Signal Processing
Volume2005
Issue number12
DOIs
StatePublished - Jul 21 2005

Keywords

  • Mean-field annealing
  • Motion estimation
  • Segmentation

ASJC Scopus subject areas

  • Signal Processing
  • Hardware and Architecture
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'An integrated dynamic scene algorithm for segmentation and motion estimation'. Together they form a unique fingerprint.

  • Cite this