Objective estimation of body condition score by modeling cow body shape from digital images
- 1 April 2011
- journal article
- research article
- Published by American Dairy Science Association in Journal of Dairy Science
- Vol. 94 (4), 2126-2137
- https://doi.org/10.3168/jds.2010-3467
Abstract
Body condition score (BCS) is considered an important tool for management of dairy cattle. The feasibility of estimating the BCS from digital images has been demonstrated in recent work. Regression machines have been successfully employed for automatic BCS estimation, taking into account information of the overall shape or information extracted on anatomical points of the shape. Despite the progress in this research area, such studies have not addressed the problem of modeling the shape of cows to build a robust descriptor for automatic BCS estimation. Moreover, a benchmark data set of images meant as a point of reference for quantitative evaluation and comparison of different automatic estimation methods for BCS is lacking. The main objective of this study was to develop a technique that was able to describe the body shape of cows in a reconstructive way. Images, used to build a benchmark data set for developing an automatic system for BCS, were taken using a camera placed above an exit gate from the milking robot. The camera was positioned at 3 m from the ground and in such a position to capture images of the rear, dorsal pelvic, and loin area of cows. The BCS of each cow was estimated on site by 2 technicians and associated to the cow images. The benchmark data set contained 286 images with associated BCS, anatomical points, and shapes. It was used for quantitative evaluation. A set of example cow body shapes was created. Linear and polynomial kernel principal component analysis was used to reconstruct shapes of cows using a linear combination of basic shapes constructed from the example database. In this manner, a cow's body shape was described by considering her variability from the average shape. The method produced a compact description of the shape to be used for automatic estimation of BCS. Model validation showed that the polynomial model proposed in this study performs better (error = 0.31) than other state-of-the-art methods in estimating BCS even at the extreme values of BCS scale.Keywords
Funding Information
- Assessorato Agricoltura e Foreste della Regione Siciliana
This publication has 25 references indexed in Scilit:
- Genetic relationships between body condition score and reproduction traits in Canadian Holstein and Ayrshire first-parity cowsJournal of Dairy Science, 2010
- Recognition of Occluded Shapes Using Size FunctionsLecture Notes in Computer Science, 2009
- Kernel PCA for similarity invariant shape recognitionNeurocomputing, 2007
- Statistical shape analysis using kernel PCAPublished by SPIE-Intl Soc Optical Eng ,2006
- Genetic Relationships among Body Condition Score, Body Weight, Milk Yield, and Fertility in Dairy CowsJournal of Dairy Science, 2003
- Shape matching and object recognition using shape contextsIeee Transactions On Pattern Analysis and Machine Intelligence, 2002
- Active appearance modelsIEEE Transactions on Pattern Analysis and Machine Intelligence, 2001
- Impact of recent research on energy feeding systems for dairy cattleLivestock Production Science, 2000
- Training Models of Shape from Sets of ExamplesPublished by British Machine Vision Association and Society for Pattern Recognition ,1992
- Active Shape Models — ‘Smart Snakes’Published by Springer Science and Business Media LLC ,1992