Assessment of Cow’s Body Condition Score Through Statistical Shape Analysis and Regression Machines

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Sebastiano Battiato, Giovanni Maria Farinella, Giuseppe Claudio Guarnera, Giovanni Puglisi, Giuseppe Azzaro, Margherita Caccamo ;
Proceedings of the First Workshop on Applications of Pattern Analysis, PMLR 11:66-73, 2010.

Abstract

This study explores the feasibility of estimating the Body Condition Score (BCS) of cows from digital images by employing statistical shape analysis and regression machines. The shapes of body cows are described through a number of variations from a unique average shape. Specifically, Kernel Principal Component Analysis is used to determine the components describing the many ways in which the body shape of different cows tend to deform from the average shape. This description is used for automatic estimation of BCS through regression approach. The proposed method has been tested on a new benchmark dataset available through the Internet. Experimental results confirm the effectiveness of the proposed technique that outperforms the state-of-the-art approaches proposed in the context of dairy cattle research.

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