Multiple animals tracking in video using part affinity fields

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Visual observation and analysis of Vertebrate And Insect Behavior 2018. 2018 Aug 20

Multiple animals tracking in video using part affinity fields Branson Lab

Rodriguez IF, Megret R, Egnor R, Branson K, Agosto JL, Giray T, Acuna E

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Abstract

In this work, we address the problem of pose detection and tracking of multiple individuals for the study of behaviour in insects and animals. Using a Deep Neural Network architecture, precise detection and association of the body parts can be performed. The models are learned based on user-annotated training videos, which gives flexibility to the approach. This is illustrated on two different animals: honeybees and mice, where very good performance in part recognition and association are observed despite the presence of multiple interacting individuals.

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Multiple animals tracking in video using part affinity fields

Abstract

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