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

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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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Authors and Affiliations

  1. Faculty of Information Technology, King Mongkut’s Institute of Technology, Ladkrabang, Thailand

    Kitsuchart Pasupa, Natapon Pantuwong & Suthasinee Nopparit

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  1. Kitsuchart Pasupa
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  2. Natapon Pantuwong
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  3. Suthasinee Nopparit
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Correspondence to Kitsuchart Pasupa.

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Pasupa, K., Pantuwong, N. & Nopparit, S. A comparative study of feature point matching versus foreground detection for computer detection of dairy cows in video frames. Artif Life Robotics 20, 320–326 (2015). https://doi.org/10.1007/s10015-015-0233-x

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  • DOI: https://doi.org/10.1007/s10015-015-0233-x

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