PARTICLE TRACKING IN BIOLOGICAL IMAGES WITH OPTICAL-FLOW ENHANCED KALMAN FILTERING - Equipe Image, Modélisation, Analyse, GEométrie, Synthèse Access content directly
Conference Papers Year : 2024

PARTICLE TRACKING IN BIOLOGICAL IMAGES WITH OPTICAL-FLOW ENHANCED KALMAN FILTERING

Abstract

Single-particle-tracking is a fundamental prerequisite for studying biological processes in time-lapse microscopy. However, it remains a challenging task in many applications where numerous particles are driven by fast and complex motion patterns. To anticipate the motion of particles most tracking algorithms usually assume near constant position, velocity or acceleration over consecutive frames. However, such assumptions are not robust to large and sudden velocity changes that typically occur in in vivo imaging. In this paper, we exploit optical flow to directly measure the velocity of particles in a Kalman filtering context. The resulting method shows improved robustness to correctly predict particles positions, even with sudden motions. We validate our method on simulated images with high particle density and fast elastic motion patterns. Quantitative results show a decrease of tracking errors by a factor of two, when compared to other tracking algorithms, while preserving fast computational time.
Fichier principal
Vignette du fichier
Kalman_and_optical_flow_filtering-1.pdf (12.53 Mo) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

pasteur-04626732 , version 1 (27-06-2024)

Identifiers

  • HAL Id : pasteur-04626732 , version 1

Cite

Raphael Reme, Alasdair Newson, Elsa Angelini, Jean-Christophe Olivo-Marin, Thibault Lagache. PARTICLE TRACKING IN BIOLOGICAL IMAGES WITH OPTICAL-FLOW ENHANCED KALMAN FILTERING. International Symposium on Biomedical Imaging (ISBI), IEEE, May 2024, Athens (Greece), France. ⟨pasteur-04626732⟩
5 View
5 Download

Share

Gmail Mastodon Facebook X LinkedIn More