3D face recognition using photometric stereo

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 explored using data captured via a photometric stereo method from the University of the West of England’s “Photoface” device. Accuracy assessments demonstrate the advantage of the capture format and the synergy offered by near infrared light sources in achieving more accurate results than under conventional visible light. Two 3D face databases have been created as part of the thesis – the publicly available Photoface database which contains 3187 images of 453 subjects and the 3DE-VISIR dataset which contains 363 images of 115 people with different expressions captured simultaneously under near infrared and visible light. The Photoface database is believed to be the ?rst to capture naturalistic 3D face models. Subsets of these databases are then used to show the results of experiments inspired by the human visual system. Experimental results show that optimal recognition rates are achieved using surprisingly low resolution of only 10x10 pixels on surface normal data, which corresponds to the spatial frequency range of optimal human performance. Motivated by the observed increase in recognition speed and accuracy that occurs in humans when faces are caricatured, novel interpretations of caricaturing using outlying data and pixel locations with high variance show that performance remains disproportionately high when up to 90% of the data has been discarded. These direct methods of dimensionality reduction have useful implications for the storage and processing requirements for commercial face recognition systems. The novel variance approach is extended to recognise positive expressions with 90% accuracy which has useful implications for human-computer interaction as well as ensuring that a subject has the correct expression prior to recognition. Furthermore, the subject recognition rate is improved by removing those pixels which encode expression. Finally, preliminary work into feature detection on surface normals by extending Haar-like features is presented which is also shown to be useful for correcting the pose of the head as part of a fully operational device. The system operates with an accuracy of 98.65% at a false acceptance rate of only 0.01 on front facing heads with neutral expressions. The work has shown how new avenues of enquiry inspired by our observation of the human visual system can offer useful advantages towards achieving more robust autonomous computer-based facial recognition

Innovative 3D and 2D machine vision methods for analysis of plants and crops in the field

© 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 approach, where the utility of the resulting data is often limited by effects such as parallax, perspective, occlusion and changes in background light – particularly when operating in the field. The 3D approach to plant and crop analysis described in this paper offers potential to obviate many of these difficulties by utilising the richer information that 3D data can generate. The methodologies presented, such as four-light photometric stereo, also provide advanced functionalities, such as an ability to robustly recover 3D surface texture from plants at very high resolution. This offers potential for enabling, for example, reliable detection of the meristem (the part of the plant where growth can take place), to within a few mm, for directed weeding (with all the associated cost and ecological benefits) as well as offering new capabilities for plant phenotyping. The considerable challenges associated with robust and reliable utilisation of machine vision in the field are also considered and practical solutions are described. Two projects are used to illustrate the proposed approaches: a four-light photometric stereo apparatus able to recover plant textures at high-resolution (even in direct sunlight), and a 3D system able to measure potato sizes in-the-field to an accuracy of within 10%, for extended periods and in a range of environmental conditions. The potential benefits of the proposed 3D methods are discussed, both in terms of the advanced capabilities attainable and the widespread potential uptake facilitated by their low cost

Photometric stereo for three-dimensional leaf venation extraction

© 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 ambient illuminations, and abnormal conditions of leaves may coexist with other complications. While leaf venation extraction has high potential for assisting with plant phenotyping, speciation and modelling, its investigations to date have been confined to colour image acquisition and processing which are commonly confounded by the aforementioned biotic and abiotic variations. To bridge the gaps in this area, we have designed a 3D imaging system for leaf venation extraction, which can overcome dark or bright ambient illumination and can allow for 3D data reconstruction in high resolution. We further propose a novel leaf venation extraction algorithm that can obtain illumination-independent surface normal features by performing Photometric Stereo reconstruction as well as local shape measures by fusing the decoupled shape index and curvedness features. In addition, this algorithm can determine venation polarity – whether veins are raised above or recessed into a leaf. Tests on both sides of different leaf species with varied venation architectures show that the proposed method is accurate in extracting the primary, secondary and even tertiary veins. It also proves to be robust against leaf diseases which can cause dramatic changes in colour. The effectiveness of this algorithm in determining venation polarity is verified by it correctly recognising raised or recessed veins in nine different experiments

A efficient and practical 3D face scanner using near infrared and visible photometric stereo

AbstractThis 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. This paper is motivated by this need and offers three primary contributions. Firstly, the paper demonstrates that four-source photometric stereo offers a potential means for data capture that is computationally nd financially viable and easily deployable in commercial settings. We have shown that both visible light and less ntrusive near infrared light is suitable for facial illumination. The second contribution is a detailed set of experimental esults that compare the accuracy of the device to ground truth, which was captured using a commercial projected pattern range finder. Importantly, we show that not only is near infrared light a valid alternative to the more commonly xploited visible light, but that it actually gives more accurate reconstructions. Finally, we assess the validity of the Lambertian assumption on skin reflectance data and show that better results may be obtained by incorporating more dvanced reflectance functions, such as the Oren–Nayar model

Towards on-farm pig face recognition using convolutional neural networks

© 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 best practice involves the use of RFID tags which are time-consuming for the farmer and distressing for the animal to fit. To overcome this, non-invasive biometrics are proposed by using the face of the animal. We test this in a farm environment, on 10 individual pigs using three techniques adopted from the human face recognition literature: Fisherfaces, the VGG-Face pre-trained face convolutional neural network (CNN) model and our own CNN model that we train using an artificially augmented data set. Our results show that accurate individual pig recognition is possible with accuracy rates of 96.7% on 1553 images. Class Activated Mapping using Grad-CAM is used to show the regions that our network uses to discriminate between pigs

Forchhammeria and Stixis (Brassicales): Stem and Wood Anatomical Diversity, Ecological and Phylogenetic Significance

Qualitative and quantitative data are given for wood anatomy of six of the 11 recognized species of Forchhammeria (Mexico, Central America, West Indies), a genus formerly placed in Capparaceae. Though still in Brassicales, the genus has been excluded, along with several other genera, from the major recognized families of that order on the basis of molecular data. Liquid-preserved material of several species permitted detailed histological accounts of the successive cambia and their development in the stems of Forchhammeria. Successive cambia have a curious distribution in Brassicales that may represent homoplasies. Most wood features of the genus do not appear highly xeromorphic, but presence of tracheids as a wood background tissue and abundance of starch and perhaps water storage in ray parenchyma and conjunctive tissue can be cited as mechanisms likely to resist embolism formation. Forchhammeria retains green leaves throughout the dry season. Forchhammeria tamaulipana, known only from Tamaulipas State, Mexico, the single species of a new subgenus, Pauciflora, is newly described. Its embryos have nearly equal cotyledons and germinate epigeously, whereas all remaining species of the genus are pseudomonocotylous and hypogeous. These and other distinctive features of F. tamaulipana may prove significant in providing links to other brassicalean genera. The family name Stixaceae Doweld is now appropriate for Forchhammeria, Neothorelia, Stixis, and Tirani

The Role of State Flex Programs in Supporting Quality Improvement in CAHs (Policy Brief #16)

This study examined QI activities supported by the Flex Program in nine states, assessed the role of the State Flex Programs in developing and supporting QI activities, and explored the effect of these initiatives on CAH QI efforts. Key Findings: The Flex Program has been instrumental in funding and providing leadership for the development of CAH quality improvement initiatives. Collaborative shared learning strategies have been central to the success of Flex Program QI programs. Scaling QI program activities to the capacity and resources of CAHs is critical to success. Administrative, clinical, and board leadership and buy-in are also critical to the success of CAH QI initiatives. Despite widespread support for these QI initiatives, there is limited hard evidence on their impact. Overlap between the quality measures in Hospital Compare and those used by state and multi-state QI reporting and benchmarking programs offers the opportunity for developing a common set of “rural relevant” hospital quality measures

Effects of Noise, Correlations and errors in the preparation of initial states in Quantum Simulations

In principle a quantum system could be used to simulate another quantum system. The purpose of such a simulation would be to obtain information about problems which cannot be simulated with a classical computer due to the exponential increase of the Hilbert space with the size of the system and which cannot be measured or controlled in an actual experiment. The system will interact with the surrounding environment, with the other particles in the system and be implemented using imperfect controls making it subject to noise. It has been suggested that noise does not need to be controlled to the same extent as it must be for general quantum computing. However the effects of noise in quantum simulations and how to treat them are not completely understood. In this paper we study an existing quantum algorithm for the one-dimensional Fano-Anderson model to be simulated using a liquid-state NMR device. We calculate the evolution of different initial states in the original model, and then we add interacting spins to simulate a more realistic situation. We find that states which are entangled with their environment, and sometimes correlated but not necessarily entangled have an evolution which is described by maps which are not completely positive. We discuss the conditions for this to occur and also the implications.Comment: Revtex 4-1, 14 pages, 21 figures, version 2 has typos corrected and acknowledgement adde

Models for Quality Improvement in CAHs: The Role of State Flex Programs (Briefing Paper #25)

A central goal of the Flex Program, as defined in the original and reauthorizing legislation, is to help Critical Access Hospitals (CAHs) develop and sustain effective quality improvement (QI) programs. This study examined the range of multi-CAH QI and performance measurement reporting initiatives supported by the Flex Program in nine states, assessed the role of State Flex Programs in developing and supporting these initiatives, and explored their impact on the QI programs of CAHs. Key Findings: State Flex Program funding was frequently the primary, if not sole, source of funding to support these efforts. Collaboration and shared learning are common Flex Program strategies underlying state QI initiatives. Quality measurement and reporting is a challenge due to a lack of agreement on common measures across state QI and benchmarking systems and a common belief that Hospital Compare measures are not “rurally relevant” (i.e., specific to the needs of CAHs). Administrative, clinical, and board leadership and buy-in were consistently identified as crucial to the success and sustainability of CAH-level QI initiatives. States reported that the scope of their QI has to be scaled to the available resources and capacity of CAHs to avoid QI fatigue among CAH staff. There is limited hard evidence on the impact of the QI initiatives adopted by State Flex Programs; much of the “evidence” supporting these initiatives is anecdotal or based on postconference or webinar evaluations

The Outbursts and Orbit of the Accreting Pulsar GS 1843-02 = 2S 1845-024

We present observations of a series of 10 outbursts of pulsed hard X-ray flux from the transient 10.6 mHz accreting pulsar GS 1843-02, using the Burst and Transient Source Experiment on the Compton Gamma Ray Observatory. These outbursts occurred regularly every 242 days, coincident with the ephemeris of the periodic transient GRO J1849-03 (Zhang et al. 1996), which has recently been identified with the SAS 3 source 2S 1845-024 (Soffitta et al. 1998). Our pulsed detection provides the first clear identification of GS 1843-02 with 2S 1845-024. We present a pulse timing analysis which shows that the 2S 1845-024 outbursts occur near the periastron passage of the neutron star's highly eccentric (e = 0.88+-0.01) 242.18+-0.01 day period binary orbit about a high mass (M > 7 solar masses) companion. The orbit and transient outburst pattern strongly suggest the pulsar is in a binary system with a Be star. Our observations show a long-term spin-up trend, with most of the spin-up occurring during the outbursts. From the measured spin-up rates and inferred luminosities we conclude that an accretion disk is present during the outbursts.Comment: Accepted for publication in Astrophysical Journa