Automatic monitoring of activity intensity in a chicken flock using a computer vision-based background image subtraction technique: An experimental infection study with fowl adenovirus

This study assessed the applicability of a background image subtraction technique for automatic monitoring of activity intensity in a chicken flock. Initially, to determine the appropriate camera shooting direction and time of day for activity analysis, two cages housing five and seven chickens were...

Full description

Saved in:
Bibliographic Details
Main Authors: Hiroshi Iseki, Eri Furukawa, Tomoya Shimasaki, Shogo Higaki
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Smart Agricultural Technology
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2772375525000553
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This study assessed the applicability of a background image subtraction technique for automatic monitoring of activity intensity in a chicken flock. Initially, to determine the appropriate camera shooting direction and time of day for activity analysis, two cages housing five and seven chickens were simultaneously video recorded from top and side perspectives. The foreground (moving object: chicken) was extracted from the videos using background subtraction, and moving pixels were counted in 5-frame-per-second sequences. Analysis of hourly averaged moving pixel ratios (total pixels of the moving object / total pixels of the region of interest) showed that the daytime top-view video was suitable. Subsequently, an experimental infection study using fowl adenovirus was performed, with four cages per infected and non-infected group, and six chickens per cage. Daytime top-view videos from –8 to 8 days post-inoculation (dpi) were analyzed and a daily activity index (average moving pixel ratio during daytime / average moving pixel ratio during daytime from –8 to –5 dpi) was calculated. Correlation analysis between the activity index and visual clinical score revealed a strong positive correlation (Pearson's correlation coefficient = 0.663). This finding indicates the potential of this method for automatic monitoring of activity intensity in a chicken flock.
ISSN:2772-3755