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Eye Centre Localisation with Convolutional Neural Network Based Regression (2019)
Conference Proceeding
Zhang, W., & Smith, M. (in press). Eye Centre Localisation with Convolutional Neural Network Based Regression

This paper introduces convolutional neural network regression models based on the Inception-v3 and the DenseNet architectures for accurate and real-time eye centre localisation. At a normalised error of e < 0.05, the proposed method yields an accurac... Read More about Eye Centre Localisation with Convolutional Neural Network Based Regression.

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.

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.

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.

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.

Eye centre localisation: An unsupervised modular approach (2016)
Journal Article
Farooq, A. R., Smith, L. N., Smith, M. L., Zhang, W., Smith, M., Smith, L., & Farooq, A. (2016). Eye centre localisation: An unsupervised modular approach. Sensor Review, 36(3), 277-286. https://doi.org/10.1108/SR-06-2015-0098

© Emerald Group Publishing Limited. Purpose - This paper aims to introduce an unsupervised modular approach for eye centre localisation in images and videos following a coarse-to-fine, global-to-regional scheme. The design of the algorithm aims at ex... Read More about Eye centre localisation: An unsupervised modular approach.

Gender recognition from facial images: Two or three dimensions? (2016)
Journal Article
Smith, L. N., Smith, M. L., Wenhao, Z., Zhang, W., Smith, M., Smith, L., & Farooq, A. (2016). Gender recognition from facial images: Two or three dimensions?. Journal of the Optical Society of America A, 33(3), 333-344. https://doi.org/10.1364/JOSAA.33.000333

© 2016 Optical Society of America. This paper seeks to compare encoded features from both two-dimensional (2D) and three-dimensional (3D) face images in order to achieve automatic gender recognition with high accuracy and robustness. The Fisher vecto... Read More about Gender recognition from facial images: Two or three dimensions?.

Eye center localization and gaze gesture recognition for human-computer interaction (2016)
Journal Article
Smith, L. N., Smith, M. L., Zhang, W., Smith, M., Smith, L., & Farooq, A. (2016). Eye center localization and gaze gesture recognition for human-computer interaction. Journal of the Optical Society of America A, 33(3), 314-325. https://doi.org/10.1364/JOSAA.33.000314

© 2016 Optical Society of America. This paper introduces an unsupervised modular approach for accurate and real-time eye center localization in images and videos, thus allowing a coarse-to-fine, global-to-regional scheme. The trajectories of eye cent... Read More about Eye center localization and gaze gesture recognition for human-computer interaction.

Gender and gaze gesture recognition for human-computer interaction (2016)
Journal Article
Zhang, W., Smith, M., Smith, L., & Farooq, A. (2016). Gender and gaze gesture recognition for human-computer interaction. Computer Vision and Image Understanding, 149, 32-50. https://doi.org/10.1016/j.cviu.2016.03.014

The identification of visual cues in facial images has been widely explored in the broad area of computer vision. However theoretical analyses are often not transformed into widespread assistive Human-Computer Interaction (HCI) systems, due to factor... Read More about Gender and gaze gesture recognition for human-computer interaction.