Feature point based 3D tracking of multiple fish from multi-view images | Zendy

Zhiming Qian | Zendy; Yan Qiu Chen | Zendy

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Feature point based 3D tracking of multiple fish from multi-view images

Author(s) -

Zhiming Qian,

Yan Qiu Chen

Publication year - 2017

Publication title -

plos one

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.99

H-Index - 332

ISSN - 1932-6203

DOI - 10.1371/journal.pone.0180254

Subject(s) - artificial intelligence , computer vision , feature (linguistics) , trajectory , tracking (education) , computer science , point (geometry) , matching (statistics) , pattern recognition (psychology) , feature matching , motion (physics) , object (grammar) , representation (politics) , video tracking , feature extraction , mathematics , geometry , physics , psychology , pedagogy , philosophy , linguistics , statistics , astronomy , politics , political science , law

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.

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