Eye centre localisation with convolutional neural networks in high- and low-resolution images (2022)
Journal Article
Zhang, W., & Smith, M. L. (2022). Eye centre localisation with convolutional neural networks in high- and low-resolution images. Lecture Notes in Artificial Intelligence, 13375 LNCS, 373-384. https://doi.org/10.1007/978-3-031-10522-7_26

Eye centre localisation is critical to eye tracking systems of various forms and with applications in variety of disciplines. An active eye tracking approach can achieve a high accuracy by leveraging active illumination to gain an enhanced contrast o... Read More about Eye centre localisation with convolutional neural networks in high- and low-resolution images.

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.

2D and 3D face analysis for ticketless rail travel (2018)
Conference Proceeding
Smith, L., Zhang, W., & Smith, M. L. (2018). 2D and 3D face analysis for ticketless rail travel. In Proceedings of the 2018 International Conference on Image Processing, Computer Vision, & Pattern Recognition. , (16-22)

Research is reported into the design, implementation and functionalities of a vision system that employs the human face as a biometric for enabling ticketless rail travel. The system has been developed to optimise performance in the relatively unstru... Read More about 2D and 3D face analysis for ticketless rail travel.

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.

Eye centre localisation: An unsupervised modular approach (2016)
Journal Article
Zhang, W., Smith, M. L., Smith, L. N., & Farooq, A. R. (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 and gaze gesture recognition for human-computer interaction (2016)
Journal Article
Zhang, W., Smith, M. L., Smith, L. N., & 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

© 2016 Elsevier Inc. 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) s... Read More about Gender and gaze gesture recognition for human-computer interaction.

Gender recognition from facial images: Two or three dimensions? (2016)
Journal Article
Zhang, W., Smith, M. L., Smith, L. N., & 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
Zhang, W., Smith, M. L., Smith, L. N., & 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.