Particle Tracking Algorithm with Spring Model

• OKAMOTO Koji

  University of Tokyo

Bibliographic Information

Other Title

• 148 バネモデル粒子追跡アルゴリズム

Abstract

The cross correlation tracking technique is widely used to analyze image data, in Particle Image Velocimetry(PIV). The technique assumes that the fluid motion, within small regions of the flow field, is parallel over short time intervals. However, actual flow fields may have some distorted motion, such as rotation, shear and expansion. In this study, A new algorithm for particle tracking, called the Spring Model technique, has been proposed. The algorithm can be applied to flow fields which exhibit characteristics such as rotation, shear and expansion.<BR>The algorithm is based on pattern matching of particle clusters between the first and second image. A particle cluster is composed of particles which are assumed to be connected by invisible elastic springs. Depending on the deformation of the cluster pattern, the invisible springs have some forces. The smallest force pattern in the second image is the most probable pattern match to the correspondent original pattern in the first image. The effectiveness of the Spring Model technique was verified with synthetic data. It showed a high degree of accuracy, even for the three-dimensional calculation. The effects of appearing and disappearing particles were treated as a penalty in the spring force calculation, showing the high efficiency of the tracking.

Journal

• Journal of the Visualization Society of Japan

  Journal of the Visualization Society of Japan 15 (Supplement2), 193-196, 1995

  The Visualization Society of Japan

Details

• CRID: 1390282679595020288
• NII Article ID: 10002673871
• NII Book ID: AN10374478
• DOI: 10.3154/jvs.15.supplement2_193
• ISSN: 1884037X
• ISSN: 09164731
• Text Lang: ja
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed