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Outputs (42)

Optimisation of small-scale aquaponics systems using artificial intelligence and the IoT: Current status, challenges, and opportunities (2024)
Journal Article
Channa, A. A., Munir, K., Hansen, M., & Tariq, M. F. (2024). Optimisation of small-scale aquaponics systems using artificial intelligence and the IoT: Current status, challenges, and opportunities. Encyclopedia, 4(1), 313-336. https://doi.org/10.3390/encyclopedia4010023

Environment changes, water scarcity, soil depletion, and urbanisation are making it harder to produce food using traditional methods in various regions and countries. Aquaponics is emerging as a sustainable food production system that produces fish a... Read More about Optimisation of small-scale aquaponics systems using artificial intelligence and the IoT: Current status, challenges, and opportunities.

Achieving goals using reward shaping and curriculum learning (2023)
Presentation / Conference
Studley, M., hansen, M., anca, M., thomas, J., & pedamonti, D. (2023, November). Achieving goals using reward shaping and curriculum learning. Paper presented at Future Technologies Conference, San Francisco

Real-time control for robotics is a popular research area in the reinforcement learning community. Through the use of techniques such as reward shaping, researchers have managed to train online agents across a multitude of domains. Despite these adva... Read More about Achieving goals using reward shaping and curriculum learning.

Embedding citizens within airborne microplastic and microfibre research (2023)
Journal Article
Williams, B., De Vito, L., Margarida Sardo, A., Pringle, K., Hansen, M., Taylor, M., …Hayes, E. (2023). Embedding citizens within airborne microplastic and microfibre research. Cambridge Prisms: Plastics, 1(e11), 1-5. https://doi.org/10.1017/plc.2023.11

Microplastics are ubiquitous in our environment but their presence in air is less well understood. Homes are likely a key source of airborne microplastics and microfibres to the environment owing to the frequent use and storage of plastics and textil... Read More about Embedding citizens within airborne microplastic and microfibre research.

Transformers and human-robot interaction for delirium detection (2023)
Conference Proceeding
Jeffcock, J., Hansen, M., & Ruiz Garate, V. (2023). Transformers and human-robot interaction for delirium detection. In 2023 ACM/IEEE International Conference on Human-Robot Interaction (466-474). https://doi.org/10.1145/3568162.3576971

An estimated 20% of patients admitted to hospital wards are affected by delirium. Early detection is recommended to treat underlying causes of delirium, however workforce strain in general wards often causes it to remain undetected. This work propose... Read More about Transformers and human-robot interaction for delirium detection.

A procedure for monitoring the phenological status of peach flowers with artificial vision (2022)
Presentation / Conference
Hansen, M., Veganzones, A., Lafuente, V., Barreiro, P., Lleo, L., & Val, J. (2022, December). A procedure for monitoring the phenological status of peach flowers with artificial vision. Paper presented at The XX CIGR World Congress 2022, Kyoto, Japan

Tree flowering is a major event in crop production as it anticipates season yield. However a number of issues may occur during the campaign such as frost, and/or irregular mineral nutrition, among other, that strongly affect this process. On the othe... Read More about A procedure for monitoring the phenological status of peach flowers with artificial vision.

Rapid identification of foodborne pathogens in limited resources settings using a handheld Raman spectroscopy device (2022)
Journal Article
Stratakos, A., & Hansen, M. (2022). Rapid identification of foodborne pathogens in limited resources settings using a handheld Raman spectroscopy device. Applied Sciences, 12(19), Article 9909. https://doi.org/10.3390/app12199909

Featured Application: Here, we report a practical and precise method for the identification of foodborne pathogenic bacteria using a Raman handheld device equipped with an orbital raster scan (ORS) technology that enables the system to generate a dis... Read More about Rapid identification of foodborne pathogens in limited resources settings using a handheld Raman spectroscopy device.

Improvements in learning to control perched landings (2022)
Journal Article
Fletcher, L., Clarke, R., Richardson, T., & Hansen, M. (2022). Improvements in learning to control perched landings. Aeronautical Journal, 126(1301), 1101-1123. https://doi.org/10.1017/aer.2022.48

Reinforcement learning has previously been applied to the problem of controlling a perched landing manoeuvre for a custom sweep-wing aircraft. Previous work showed that the use of domain randomisation to train with atmospheric disturbances improved t... Read More about Improvements in learning to control perched landings.

Towards machine vision for insect welfare monitoring and behavioural insights (2022)
Journal Article
Hansen, M. F., Oparaeke, A., Gallagher, R., Karimi, A., Tariq, F., & Smith, M. L. (2022). Towards machine vision for insect welfare monitoring and behavioural insights. Frontiers in Veterinary Science, 9, Article 835529. https://doi.org/10.3389/fvets.2022.835529

Machine vision has demonstrated its usefulness in the livestock industry in terms of improving welfare in such areas as lameness detection and body condition scoring in dairy cattle. In this article, we present some promising results of applying stat... Read More about Towards machine vision for insect welfare monitoring and behavioural insights.

Vision based semantic runway segmentation from simulation with deep convolutional neural networks (2021)
Conference Proceeding
Quessy, A. D., Richardson, T. S., & Hansen, M. (2022). Vision based semantic runway segmentation from simulation with deep convolutional neural networks. https://doi.org/10.2514/6.2022-0680

Manned flight crew rely upon optical imagery to make sense of the world and carry out high level guidance, navigation & control tasks. To advance autonomous aircraft’s capabilities and safety, programmes need to be developed that aim to achieve pilot... Read More about Vision based semantic runway segmentation from simulation with deep convolutional neural networks.

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. (2021). Towards facial expression recognition for on-farm welfare assessment in pigs. Agriculture, 11(9), Article 847. 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.

Contactless robust 3D palm-print identification using photometric stereo (2021)
Conference Proceeding
Smith, L. N., Langhof, M. P., Hansen, M. F., & Smith, M. L. (2021). Contactless robust 3D palm-print identification using photometric stereo. https://doi.org/10.1117/12.2595439

Palmprints are of considerable interest as a reliable biometric, since they offer significant advantages, such as greater user acceptance than fingerprint or iris recognition. 2D systems can be spoofed by a photograph of a hand; however, 3D avoids th... Read More about Contactless robust 3D palm-print identification using photometric stereo.

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, Article 103472. 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.

Reinforcement learning for a perched landing in the presence of wind (2021)
Conference Proceeding
Fletcher, L. J., Clarke, R. J., Richardson, T. S., & Hansen, M. (2021). Reinforcement learning for a perched landing in the presence of wind. . https://doi.org/10.2514/6.2021-1282

Previous research by the University of Bristol's Flight Lab demonstrated the feasibility of using reinforcement learning to generate a controller to perform an agile perched landing flight manoeuvre. However, flight testing demonstrated the limits of... Read More about Reinforcement learning for a perched landing in the presence of wind.

Image segmentation of underfloor scenes using a mask regions convolutional neural network with two-stage transfer learning (2020)
Journal Article
Atkinson, G. A., Zhang, W., Hansen, M. F., Holloway, M. L., & Napier, A. A. (2020). Image segmentation of underfloor scenes using a mask regions convolutional neural network with two-stage transfer learning. Automation in Construction, 113, Article 103118. https://doi.org/10.1016/j.autcon.2020.103118

© 2020 Elsevier B.V. Enclosed spaces are common in built structures but pose a challenge to many forms of manual or robotic surveying and maintenance tasks. Part of this challenge is to train robot systems to understand their environment without huma... Read More about Image segmentation of underfloor scenes using a mask regions convolutional neural network with two-stage transfer learning.

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, Article 4. 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), Article giz056. 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, Las Vegas, USA

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), Cancun, Mexico

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. L., & Smith, L. N. (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

© 2016 IAgrE Lameness is a major issue in dairy herds and its early and automated detection offers animal welfare benefits together with potentially high commercial savings for farmers. Current advancements in automated detection have not achieved a... 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), Tokyo, Japan

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, Newcastle, UK

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, Swansea, Wales, UK

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
Williamson, D. R., Hales, I. J., Hansen, M. F., Broadbent, L., & 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, York, UK

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.

Face recognition and verification using photometric stereo: The photoface database and a comprehensive evaluation (2013)
Journal Article
Smith, L. N., Smith, M. L., Hansen, M. F., Atkinson, G. A., Zafeiriou, S., Atkinson, G., …Smith, L. (2013). Face recognition and verification using photometric stereo: The photoface database and a comprehensive evaluation. IEEE Transactions on Information Forensics and Security, 8(1), 121-135. https://doi.org/10.1109/TIFS.2012.2224109

This paper presents a new database suitable for both 2-D and 3-D face recognition based on photometric stereo (PS): the Photoface database. The database was collected using a custom-made four-source PS device designed to enable data capture with mini... Read More about Face recognition and verification using photometric stereo: The photoface database and a comprehensive evaluation.

3D face recognition using photometric stereo (2012)
Thesis
Hansen, M. F. 3D face recognition using photometric stereo. (Thesis). University of the West of England. Retrieved from https://uwe-repository.worktribe.com/output/947596

Automatic face recognition has been an active research area for the last four decades. This thesis explores innovative bio-inspired concepts aimed at improved face recognition using surface normals. New directions in salient data representation are e... Read More about 3D face recognition using photometric stereo.

Twins 3D face recognition challenge (2011)
Presentation / Conference
Vijayan, V., Bowyer, K. W., Flynn, P. J., Huang, D. S., Chen, L., Hansen, M. F., …Kakadiaris, I. (2011, October). Twins 3D face recognition challenge. Paper presented at International Joint Conference on Biometrics, Washington DC, USA

Existing 3D face recognition algorithms have achieved high enough performances against public datasets like FRGC v2, that it is difficult to achieve further significant increases in recognition performance. However, the 3D TEC dataset is a more chall... Read More about Twins 3D face recognition challenge.

Psychologically inspired dimensionality reduction for 2D and 3D Face Recognition (2011)
Presentation / Conference
Hansen, M. F., Atkinson, G., Smith, M., & Smith, L. (2011, September). Psychologically inspired dimensionality reduction for 2D and 3D Face Recognition. Paper presented at British Machine Vision Conference 2011, Dundee, UK

We present a number of related novel methods for reducing the dimensionality of data for the purposes of 2D and 3D face recognition. Results from psychology show that humans are capable of very good recognition of low resolution images and caricature... Read More about Psychologically inspired dimensionality reduction for 2D and 3D Face Recognition.

The photoface database (2011)
Presentation / Conference
Zafeirou, S., Hansen, M. F., Atkinson, G., Argyriou, V., Petrou, M., Smith, M., & Smith, L. (2011, June). The photoface database. Paper presented at Biometrics Workshop of Computer Vision and Pattern Recognition, Colorado Springs, Colorado, USA

Biologically inspired 3D face recognition from surface normals (2010)
Presentation / Conference
Hansen, M. F., & Atkinson, G. (2010, September). Biologically inspired 3D face recognition from surface normals. Paper presented at Procedia Computer Science, Coimbatore, India

A major consideration in state-of-the-art face recognition systems is the amount of data that is required to represent a face. Even a small (64 × 64) photograph of a face has 2 12 dimensions in which a face may sit. When large (> 1MB) photographs of... Read More about Biologically inspired 3D face recognition from surface normals.

Baseline face recognition using photometric stereo data (2010)
Presentation / Conference
Zafeiriou, S., Hansen, M. F., Atkinson, G., Petrou, M., & Smith, M. (2010, September). Baseline face recognition using photometric stereo data. Paper presented at International Conference and Exhibition on Biometrics Technology, Coimbatore, Tamil Nadu, India, 2010, Coimbatore, Tamil Nadu, India

An efficient and practical 3D face scanner using near infrared and visible photometric stereo (2010)
Presentation / Conference
Atkinson, G., Hansen, M. F., Smith, M., & Smith, L. (2010, September). An efficient and practical 3D face scanner using near infrared and visible photometric stereo. Paper presented at International Conference and Exhibition on Biometrics Technology, Coimbatore, India

This paper is concerned with the acquisition of model data for automatic 3D face recognition applications. As 3D methods become progressively more popular in face recognition research, the need for fast and accurate data capture has become crucial. T... Read More about An efficient and practical 3D face scanner using near infrared and visible photometric stereo.

3D face reconstructions from photometric stereo using near infrared and visible light (2010)
Journal Article
Hansen, M. F., Atkinson, G., Smith, L., & Smith, M. (2010). 3D face reconstructions from photometric stereo using near infrared and visible light. Computer Vision and Image Understanding, 114(8), 942-951. https://doi.org/10.1016/j.cviu.2010.03.001

This paper seeks to advance the state-of-the-art in 3D face capture and processing via novel Photometric Stereo (PS) hardware and algorithms. The first contribution is a new high-speed 3D data capture system, which is capable of acquiring four raw im... Read More about 3D face reconstructions from photometric stereo using near infrared and visible light.