Literature DB >> 25381022

A Kinect-based system for automatic recording of some pigeon behaviors.

Damian M Lyons1,2, James S MacDonall3, Kelly M Cunningham3.   

Abstract

Contact switches and touch screens are the state of the art for recording pigeons' pecking behavior. Recording other behavior, however, requires a different sensor for each behavior, and some behaviors cannot easily be recorded. We present a flexible and inexpensive image-based approach to detecting and counting pigeon behaviors that is based on the Kinect sensor from Microsoft. Although the system is as easy to set up and use as the standard approaches, it is more flexible because it can record behaviors in addition to key pecking. In this article, we show how both the fast, fine motion of key pecking and the gross body activity of feeding can be measured. Five pigeons were trained to peck at a lighted contact switch, a pigeon key, to obtain food reward. The timing of the pecks and the food reward signals were recorded in a log file using standard equipment. The Kinect-based system, called BehaviorWatch, also measured the pecking and feeding behavior and generated a different log file. For key pecking, BehaviorWatch had an average sensitivity of 95% and a precision of 91%, which were very similar to the pecking measurements from the standard equipment. For detecting feeding activity, BehaviorWatch had a sensitivity of 95% and a precision of 97%. These results allow us to demonstrate that an advantage of the Kinect-based approach is that it can also be reliably used to measure activity other than key pecking.

Keywords:  Key pecking; Kinect; Vision detecting behavior

Mesh:

Year:  2015        PMID: 25381022     DOI: 10.3758/s13428-014-0531-6

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  2 in total

1.  MarmoDetector: A novel 3D automated system for the quantitative assessment of marmoset behavior.

Authors:  Taiki Yabumoto; Fumiaki Yoshida; Hideaki Miyauchi; Kousuke Baba; Hiroshi Tsuda; Kensuke Ikenaka; Hideki Hayakawa; Nozomu Koyabu; Hiroki Hamanaka; Stella M Papa; Masayuki Hirata; Hideki Mochizuki
Journal:  J Neurosci Methods       Date:  2019-04-01       Impact factor: 2.390

2.  Automated measurement of mouse social behaviors using depth sensing, video tracking, and machine learning.

Authors:  Weizhe Hong; Ann Kennedy; Xavier P Burgos-Artizzu; Moriel Zelikowsky; Santiago G Navonne; Pietro Perona; David J Anderson
Journal:  Proc Natl Acad Sci U S A       Date:  2015-09-09       Impact factor: 11.205

  2 in total

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