Feature Point Based 3D Tracking of Multiple Fish from Multi-view Images

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2017 Jul 1

PMID 28665966

Citations 6

Authors

Zhi-Ming Qian

Yan Qiu Chen

Affiliations

Soon will be listed here.

Abstract

A feature point based method is proposed for tracking multiple fish in 3D space. First, a simplified representation of the object is realized through construction of two feature point models based on its appearance characteristics. After feature points are classified into occluded and non-occluded types, matching and association are performed, respectively. Finally, the object's motion trajectory in 3D space is obtained through integrating multi-view tracking results. Experimental results show that the proposed method can simultaneously track 3D motion trajectories for up to 10 fish accurately and robustly.

Citing Articles

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Feature Point Extraction and Motion Tracking of Cardiac Color Ultrasound under Improved Lucas-Kanade Algorithm.

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