PlantTracing: Tracing Arabidopsis Thaliana Apex with CenterTrack

TL;DR

This paper introduces PlantTracing, a machine learning approach using CenterTrack to detect and track Arabidopsis Thaliana apex growth from time-lapsed videos, enabling precise plant growth analysis.

Contribution

It adapts CenterTrack for plant apex tracking, providing a novel application of object tracking in plant phenotyping.

Findings

Successful detection and tracking of plant apex in videos

High accuracy demonstrated on test videos

Effective adaptation of CenterTrack for biological data

Abstract

This work applies an encoder-decoder-based machine learning network to detect and track the motion and growth of the flowering stem apex of Arabidopsis Thaliana. Based on the CenterTrack, a machine learning back-end network, we trained a model based on ten time-lapsed labeled videos and tested against three videos.