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Published in: Artificial Life and Robotics 4/2015

01-12-2015 | Original Article

A comparative study of feature point matching versus foreground detection for computer detection of dairy cows in video frames

Authors: Kitsuchart Pasupa, Natapon Pantuwong, Suthasinee Nopparit

Published in: Artificial Life and Robotics | Issue 4/2015

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Abstract

Behaviours of dairy cows reflect their health and emotions. Behavioural analysis by video surveillance is an accepted technique for helping cow-keepers to spot their cows' health problems. To perform a behavioural analysis, the presence and location of the cows need to be detected first. In this study, we used feature point matching method and foreground detection method to detect them. Two experiments were conducted in a dairy farm to detect cows in video frames recorded by a video camera installed over the top of a free-stall barn. A total of 800 frames of recorded cows' activities were captured. True and false positive and negative results were statistically confirmed by t test. We found that the accuracies of the feature point matching and foreground detection methods were 38.55 and 75.95 %, respectively; hence, for our setup, the foreground detection was a better method.

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Metadata
Title
A comparative study of feature point matching versus foreground detection for computer detection of dairy cows in video frames
Authors
Kitsuchart Pasupa
Natapon Pantuwong
Suthasinee Nopparit
Publication date
01-12-2015
Publisher
Springer Japan
Published in
Artificial Life and Robotics / Issue 4/2015
Print ISSN: 1433-5298
Electronic ISSN: 1614-7456
DOI
https://doi.org/10.1007/s10015-015-0233-x

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