Analysis of Dogs’ Sleep Patterns Using Convolutional Neural Networks

Anna Zamansky, Aleksandr Sinitca, Dmitry Kaplun, Michael Plazner, Ivana Gabriela Schork, Robert John Young

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract

Video-based analysis is one of the most important tools of animal behavior and animal welfare scientists. While automatic analysis systems exist for many species, this problem has not yet been adequately addressed for one of the most studied species in animal science—dogs. In this paper we describe a system developed for analyzing sleeping patterns of kenneled dogs, which may serve as indicator of their welfare. The system combines convolutional neural networks with classical data processing methods, and works with very low quality video from cameras installed in dogs shelters.
Original languageEnglish
Title of host publicationLecture Notes in Computer Science
Subtitle of host publicationArtificial Neural Networks and Machine Learning – ICANN 2019: Image Processing.
EditorsI. Tekto, V. Kurkova, P. Karpov
PublisherSpringer Nature
Volume11729
DOIs
Publication statusPublished - 9 Sep 2019
Externally publishedYes

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