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Towards facial expression recognition for on-farm welfare assessment in pigs (2021)
Journal Article
Hansen, M. F., Baxter, E. M., Rutherford, K. M. D., Futro, A., Smith, M. L., & Smith, L. N. (in press). Towards facial expression recognition for on-farm welfare assessment in pigs. Agriculture, 11(9), https://doi.org/10.3390/agriculture11090847

Animal welfare is not only an ethically important consideration in good animal husbandry but can also have a significant effect on an animal’s productivity. The aim of this paper was to show that a reduction in animal welfare, in the form of increase... Read More about Towards facial expression recognition for on-farm welfare assessment in pigs.

The quiet revolution in machine vision - A state-of-the-art survey paper, including historical review, perspectives, and future directions (2021)
Journal Article
Smith, M. L., Smith, L. N., & Hansen, M. F. (2021). The quiet revolution in machine vision - A state-of-the-art survey paper, including historical review, perspectives, and future directions. Computers in Industry, 130, https://doi.org/10.1016/j.compind.2021.103472

Over the past few years, what might not unreasonably be described as a true revolution has taken place in the field of machine vision, radically altering the way many things had previously been done and offering new and exciting opportunities for tho... Read More about The quiet revolution in machine vision - A state-of-the-art survey paper, including historical review, perspectives, and future directions.

Shedding smart light on the effectiveness of chemotherapy: using Raman spectroscopy and machine learning to differentiate the effects of Cytarabine toxicity and crosstalk of leukaemic and bone marrow stromal cells (2021)
Journal Article
Gynn, L., Lamb-Riddell, K., Cox, T., Hansen, M., Conway, M., & May, J. (2021). Shedding smart light on the effectiveness of chemotherapy: using Raman spectroscopy and machine learning to differentiate the effects of Cytarabine toxicity and crosstalk of leukaemic and bone marrow stromal cells. British Journal of Haematology, 193(S1), 46-47

Mesenchymal stromal cells (MSC) protect leukaemic cells from drug-induced toxicity within the bone marrow niche, with increasing evidence of leukaemic impact on supportive stroma. The nucleoside analogue, cytarabine (ara-C), is a front-line agent for... Read More about Shedding smart light on the effectiveness of chemotherapy: using Raman spectroscopy and machine learning to differentiate the effects of Cytarabine toxicity and crosstalk of leukaemic and bone marrow stromal cells.

Weed classification in grasslands using convolutional neural networks (2019)
Conference Proceeding
Smith, L. N., Byrne, A., Hansen, M. F., Zhang, W., & Smith, M. L. (2019). Weed classification in grasslands using convolutional neural networks. https://doi.org/10.1117/12.2530092

Automatic identification and selective spraying of weeds (such as dock) in grass can provide very significant long-term ecological and cost benefits. Although machine vision (with interface to suitable automation) provides an effective means of achie... Read More about Weed classification in grasslands using convolutional neural networks.

Surface normals based landmarking for 3D face recognition using photometric stereo captures (2019)
Conference Proceeding
Gao, J., Hansen, M., Smith, M., & Evans, A. N. (2019). Surface normals based landmarking for 3D face recognition using photometric stereo captures. In Proceedings of the 2019 3rd International Conference on Biometric Engineering and Applications. , (43-47). https://doi.org/10.1145/3345336.3345339

In recent decades, many 3D data acquisition methods have been developed to provide accurate and cost-effective 3D captures of the human face. An example system, which can accommodate both research and commercial applications, is the Photoface device.... Read More about Surface normals based landmarking for 3D face recognition using photometric stereo captures.

Multispectral imaging for presymptomatic analysis of light leaf spot in oilseed rape (2019)
Journal Article
Veys, C., Chatziavgerinos, F., AlSuwaidi, A., Hibbert, J., Hansen, M., Bernotas, G., …Grieve, B. (2019). Multispectral imaging for presymptomatic analysis of light leaf spot in oilseed rape. Plant Methods, 15, https://doi.org/10.1186/s13007-019-0389-9

Background: The use of spectral imaging within the plant phenotyping and breeding community has been increasing due its utility as a non-invasive diagnostic tool. However, there is a lack of imaging systems targeted specifically at plant science duti... Read More about Multispectral imaging for presymptomatic analysis of light leaf spot in oilseed rape.

A photometric stereo-based 3D imaging system using computer vision and deep learning for tracking plant growth (2019)
Journal Article
Bernotas, G., Scorza, L. C., Hansen, M. F., Hales, I. J., Halliday, K. J., Smith, L. N., …McCormick, A. J. (2019). A photometric stereo-based 3D imaging system using computer vision and deep learning for tracking plant growth. GigaScience, 8(5), https://doi.org/10.1093/gigascience/giz056

© The Author(s) 2019. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distri... Read More about A photometric stereo-based 3D imaging system using computer vision and deep learning for tracking plant growth.

Broad-leaf weed detection in pasture (2018)
Conference Proceeding
Zhang, W., Hansen, M. F., Volonakis, T. N., Smith, M., Smith, L., Wilson, J., …Wright, G. (2018). Broad-leaf weed detection in pasture

Weed control in pasture is a challenging problem that can be expensive and environmentally unfriendly. This paper proposes a novel method for recognition of broad-leaf weeds in pasture such that precision weed control can be achieved with reduced her... Read More about Broad-leaf weed detection in pasture.

Multispectral contactless 3D handprint acquisition for identification (2018)
Presentation / Conference
Hansen, M. F., Smith, L., & Smith, M. (2018, July). Multispectral contactless 3D handprint acquisition for identification. Paper presented at The 20th International Conference on Artificial Intelligence, 2018 World Congress in Computer Science, Computer Engineering, & Applied Computing

We present and experimentally demonstrate the potential effectiveness of a photometric stereo based high resolution system for capturing 3D handprints using visible light sources. The sub-surface vascular structures are also enhanced through the use... Read More about Multispectral contactless 3D handprint acquisition for identification.

Towards on-farm pig face recognition using convolutional neural networks (2018)
Journal Article
Baxter, E. M., Salter, M. G., Smith, L. N., Smith, M. L., Hansen, M. F., Hansen, M. F., …Grieve, B. (2018). Towards on-farm pig face recognition using convolutional neural networks. Computers in Industry, 98, 145-152. https://doi.org/10.1016/j.compind.2018.02.016

© 2018 Elsevier B.V. Identification of individual livestock such as pigs and cows has become a pressing issue in recent years as intensification practices continue to be adopted and precise objective measurements are required (e.g. weight). Current b... Read More about Towards on-farm pig face recognition using convolutional neural networks.

Innovative 3D and 2D machine vision methods for analysis of plants and crops in the field (2018)
Journal Article
Smith, L., Zhang, W., Hansen, M. F., Hales, I., & Smith, M. (2018). Innovative 3D and 2D machine vision methods for analysis of plants and crops in the field. Computers in Industry, 97, 122-131. https://doi.org/10.1016/j.compind.2018.02.002

© 2018 Elsevier B.V. Machine vision systems offer great potential for automating crop control, harvesting, fruit picking, and a range of other agricultural tasks. However, most of the reported research on machine vision in agriculture involves a 2D a... Read More about Innovative 3D and 2D machine vision methods for analysis of plants and crops in the field.

Photometric stereo for three-dimensional leaf venation extraction (2018)
Journal Article
Zhang, W., Hansen, M. F., Smith, M., Smith, L., & Grieve, B. (2018). Photometric stereo for three-dimensional leaf venation extraction. Computers in Industry, 98, 56-67. https://doi.org/10.1016/j.compind.2018.02.006

© 2018 Elsevier B.V. Leaf venation extraction studies have been strongly discouraged by considerable challenges posed by venation architectures that are complex, diverse and subtle. Additionally, unpredictable local leaf curvatures, undesirable ambie... Read More about Photometric stereo for three-dimensional leaf venation extraction.

Automated monitoring of dairy cow body condition, mobility and weight using a single 3D video capture device (2018)
Journal Article
Hansen, M. F., Smith, M. L., Smith, L. N., Abdul Jabbar, K., & Forbes, D. (2018). Automated monitoring of dairy cow body condition, mobility and weight using a single 3D video capture device. Computers in Industry, 98, 14-22. https://doi.org/10.1016/j.compind.2018.02.011

© 2018 Here we propose a low-cost automated system for the unobtrusive and continuous welfare monitoring of dairy cattle on the farm. We argue that effective and regular monitoring of multiple condition traits is not currently practicable and go on t... Read More about Automated monitoring of dairy cow body condition, mobility and weight using a single 3D video capture device.

Locomotion traits of dairy cows from overhead three-dimensional video (2016)
Presentation / Conference
Abdul Jabbar, K., Hansen, M. F., Smith, M., & Smith, L. (2016, December). Locomotion traits of dairy cows from overhead three-dimensional video. Paper presented at Visual observation and analysis of Vertebrate And Insect Behavior (VAIB), 23rd International Conference on Pattern Recognition (ICPR)

We investigate two locomotion traits in dairy cows from overhead 3D video to observe lameness trends. Detecting lameness -particularly at an early stage- is important in order to allow early treatment which maximizes detection benefits. The proposed... Read More about Locomotion traits of dairy cows from overhead three-dimensional video.

Early and non-intrusive lameness detection in dairy cows using 3-dimensional video (2016)
Journal Article
Abdul Jabbar, K., Hansen, M. F., Smith, M., & Smith, L. (2017). Early and non-intrusive lameness detection in dairy cows using 3-dimensional video. Biosystems Engineering, 153, 63-69. https://doi.org/10.1016/j.biosystemseng.2016.09.017

ABSTRACT Lameness is a major issue in dairy herds and its early and automated detection offers animal welfare benefits together with high potential commercial savings for farmers. Current advancements in automated detection have not achieved a sensi... Read More about Early and non-intrusive lameness detection in dairy cows using 3-dimensional video.

Overhead spine arch analysis of dairy cows from three-dimensional video (2016)
Presentation / Conference
Abdul Jabbar, K., Hansen, M. F., Smith, M., & Smith, L. (2016, October). Overhead spine arch analysis of dairy cows from three-dimensional video. Paper presented at Eighth International Conference on Graphic and Image Processing (ICGIP 2016)

We present a spine arch analysis method in dairy cows using overhead 3D video data. This method is aimed for early stage lameness detection. That is important in order to allow early treatment; and thus, reduce the animal suffering and minimize the h... Read More about Overhead spine arch analysis of dairy cows from three-dimensional video.

Quadruped locomotion analysis using three-dimensional video (2016)
Presentation / Conference
Abdul Jabbar, K., Hansen, M. F., Smith, M., & Smith, L. (2016, October). Quadruped locomotion analysis using three-dimensional video. Paper presented at IEEE ICSAE Conference

Abstract— To date, there has not been a single method suitable for large-scale or regular-basis implementation to analyze the locomotion of quadruped animals. Existing methods are not sensitive enough for detecting minor deviations from healthy gait... Read More about Quadruped locomotion analysis using three-dimensional video.

Non-intrusive automated measurement of dairy cow body condition using 3D video (2015)
Presentation / Conference
Hansen, M. F., Smith, M., Smith, L., & Hales, I. (2015, September). Non-intrusive automated measurement of dairy cow body condition using 3D video. Presented at British Machine Vision Conference - Workshop of Machine Vision and Animal Behaviour

Regular scoring of a dairy herd in terms of various physical metrics such as Body Condition Score (BCS), mobility and weight are essential for maintaining high animal welfare. This paper presents preliminary results of an automated system capable of... Read More about Non-intrusive automated measurement of dairy cow body condition using 3D video.

Long-range concealed object detection through active covert illumination (2015)
Journal Article
Hansen, M. F., Williamson, D. R., Hales, I. J., Hales, I. J., Williamson, D. R., Hansen, M. F., …Smith, M. (2015). Long-range concealed object detection through active covert illumination. Proceedings of SPIE, 9648, https://doi.org/10.1117/12.2190194

© 2015 SPIE. When capturing a scene for surveillance, the addition of rich 3D data can dramatically improve the accuracy of object detection or face recognition. Traditional 3D techniques, such as geometric stereo, only provide a coarse grained recon... Read More about Long-range concealed object detection through active covert illumination.

BRDF estimation for faces from a sparse dataset using a neural network (2013)
Presentation / Conference
Hansen, M. F., Atkinson, G., & Smith, M. (2013, August). BRDF estimation for faces from a sparse dataset using a neural network. Paper presented at Computer Analysis of Images and Patterns, CAIP 2013

We present a novel �ve source near-infrared photometric stereo 3D face capture device. The accuracy of the system is demonstrated by a comparison with ground truth from a commercial 3D scanner. We also use the data from the �ve captured images to mo... Read More about BRDF estimation for faces from a sparse dataset using a neural network.