Login (DCU Staff Only)
Login (DCU Staff Only)

DORAS | DCU Research Repository

Explore open access research and scholarly works from DCU

Advanced Search

Segmentation enhanced lameness detection in dairy cows from RGB and depth video

Arazo, Eric, Aly, Robin orcid logoORCID: 0000-0002-6787-0911 and McGuinness, Kevin orcid logoORCID: 0000-0003-1336-6477 (2022) Segmentation enhanced lameness detection in dairy cows from RGB and depth video. In: Workshop on Computer Vision for Animal Behavior Tracking and Modeling (CV4Animals), conference of Computer Vision and Pattern Recognition (CVPR), 20 June 2022, New Orleans, USA.

Abstract
Cow lameness is a severe condition that affects the life cycle and life quality of dairy cows and results in considerable economic losses. Early lameness detection helps farmers address illnesses early and avoid negative effects caused by the degeneration of cows' condition. We collected a dataset of short clips of cows passing through a hallway exiting a milking station and annotated the degree of lameness of the cows. This paper explores the resulting dataset and provides a detailed description of the data collection process. Additionally, we proposed a lameness detection method that leverages pre-trained neural networks to extract discriminative features from videos and assign a binary score to each cow indicating its condition: ``healthy" or ``lame." We improve this approach by forcing the model to focus on the structure of the cow, which we achieve by substituting the RGB videos with binary segmentation masks predicted with a trained segmentation model. This work aims to encourage research and provide insights into the applicability of computer vision models for cow lameness detection on farms.
Metadata
Item Type:Conference or Workshop Item (Poster)
Event Type:Workshop
Refereed:Yes
Additional Information:In conjunction with Computer Vision and Pattern Recognition 2022
Uncontrolled Keywords:Computer vision; Animal farming; Dairy cow; Lameness detection; Video segmentation
Subjects:Computer Science > Image processing
Computer Science > Machine learning
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Published in: CV4Animals: Computer Vision for Animal Behavior Tracking and Modeling, Proceedings. . CV4.
Publisher:CV4
Official URL:https://www.cv4animals.com/
Copyright Information:© 2022 The Authors.
Funders:Science Foundation Ireland (SFI) under grant number SFI/15/SIRG/3283 and SFI/12/RC/2289_P2
ID Code:27302
Deposited On:17 Jun 2022 13:45 by Eric Arazo Sánchez . Last Modified 16 Nov 2023 13:42
Documents

Full text available as:

[thumbnail of 2022_CV4Animals_CVPRw_Lameness_detection.pdf]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Creative Commons: Attribution-Noncommercial 4.0
3MB
Downloads

Downloads

Downloads per month over past year

Archive Staff Only: edit this record