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Trainable, vision-based automated home cage behavioral phenotyping

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Thomas SerreAuthors Info & Claims

MB '10: Proceedings of the 7th International Conference on Methods and Techniques in Behavioral Research

Article No.: 33, Pages 1 - 4

https://doi.org/10.1145/1931344.1931377

Published: 24 August 2010 Publication History

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Abstract

We describe a fully trainable computer vision system enabling the automated analysis of complex mouse behaviors. Our system computes a sequence of feature descriptors for each video sequence and a classifier is used to learn a mapping from these features to behaviors of interest. We collected a very large manually annotated video database of mouse behaviors for training and testing the system. Our system performs on par with human scoring, as measured from the ground-truth manual annotations of thousands of clips of freely behaving mice. As a validation of the system, we characterized the home cage behaviors of two standard inbred and two nonstandard mouse strains. From this data, we were able to predict the strain identity of individual mice with high accuracy.

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Bowley CAndes AEllis-Felege SDesell T(2016)Detecting wildlife in uncontrolled outdoor video using convolutional neural networks2016 IEEE 12th International Conference on e-Science (e-Science)10.1109/eScience.2016.7870906(251-259)Online publication date: Oct-2016
https://doi.org/10.1109/eScience.2016.7870906
Desell TBergman RGoehner KMarsh RVanderClute REllis-Felege S(2013)Wildlife@HomeProceedings of the 2013 IEEE 9th International Conference on e-Science10.1109/eScience.2013.50(107-115)Online publication date: 22-Oct-2013
https://dl.acm.org/doi/10.1109/eScience.2013.50
Farah RLanglois JBilodeau G(2013)Catching a Rat by Its EdgletsIEEE Transactions on Image Processing10.1109/TIP.2012.222172622:2(668-678)Online publication date: 1-Feb-2013
https://dl.acm.org/doi/10.1109/TIP.2012.2221726

Index Terms

Trainable, vision-based automated home cage behavioral phenotyping
1. Computing methodologies
  1. Machine learning

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Published In

MB '10: Proceedings of the 7th International Conference on Methods and Techniques in Behavioral Research

August 2010

183 pages

ISBN:9781605589268

DOI:10.1145/1931344

Editors:
Emilia Barakova
User Experiences Department, Philips Research Europe, The Netherlands
,
Boris de Ruyter
Faculty of Industrial Design, Eindhoven University of Technology, The Netherlands
,
Andrew Spink
Noldus Information Technology, The Netherlands

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 24 August 2010

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Measuring Behavior

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Measuring Behavior: Selected papers from the Proceedings of the 7th International Conference on Methods and Techniques in Behavioral research

August 24 - 27, 2010

Eindhoven, The Netherlands

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Bowley CAndes AEllis-Felege SDesell T(2016)Detecting wildlife in uncontrolled outdoor video using convolutional neural networks2016 IEEE 12th International Conference on e-Science (e-Science)10.1109/eScience.2016.7870906(251-259)Online publication date: Oct-2016
https://doi.org/10.1109/eScience.2016.7870906
Desell TBergman RGoehner KMarsh RVanderClute REllis-Felege S(2013)Wildlife@HomeProceedings of the 2013 IEEE 9th International Conference on e-Science10.1109/eScience.2013.50(107-115)Online publication date: 22-Oct-2013
https://dl.acm.org/doi/10.1109/eScience.2013.50
Farah RLanglois JBilodeau G(2013)Catching a Rat by Its EdgletsIEEE Transactions on Image Processing10.1109/TIP.2012.222172622:2(668-678)Online publication date: 1-Feb-2013
https://dl.acm.org/doi/10.1109/TIP.2012.2221726

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Design and evaluation of interaction models for multi-touch mice

Representing Honey Bee Behavior for Recognition Using Human Trainable Models

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