Abstract
Automatic cow identification becomes increasingly important for individual real time monitoring of production, health, behaviour etc., in modern dairy cattle production systems with large herd sizes. Examples of camera based classification of lameness (Viazzi et al., 2013) and conformation traits (Salau et al., 2017) have already been presented.
The aim of this study was to identify cows individually at the feeding table using a 3D camera system (Patent no: WO 2017/001538). The purpose of this identification was, with use of the same 3D camera system, to measure the feed intake for the identified cow (Lassen et al., 2017). However, the cow-id identification can also be used in combination with other features. A 3D geometric cow model with corresponding cow-id was used as reference. All cows in this study were labelled with unique cow-id, making it possible to calculate the success rate for 3D cow-id identification system
The aim of this study was to identify cows individually at the feeding table using a 3D camera system (Patent no: WO 2017/001538). The purpose of this identification was, with use of the same 3D camera system, to measure the feed intake for the identified cow (Lassen et al., 2017). However, the cow-id identification can also be used in combination with other features. A 3D geometric cow model with corresponding cow-id was used as reference. All cows in this study were labelled with unique cow-id, making it possible to calculate the success rate for 3D cow-id identification system
Original language | English |
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Publication date | 2018 |
Publication status | Published - 2018 |
Event | ICAR Conference and World Congress on Genetics Applied to Livestock Production 2018 - Auckland, New Zealand Duration: 11 Feb 2018 → 16 Feb 2018 Conference number: 11 |
Conference
Conference | ICAR Conference and World Congress on Genetics Applied to Livestock Production 2018 |
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Number | 11 |
Country/Territory | New Zealand |
City | Auckland |
Period | 11/02/2018 → 16/02/2018 |