Cross-Spectral Face Recognition Between Near-Infrared and Visible Light Modalities.

In this thesis, improvement of face recognition performance with the use of images from the visible (VIS) and near-infrared (NIR) spectrum is attempted. Face recognition systems can be adversely affected by scenarios which encounter a significant amount of illumination variation across images of the same subject. Cross-spectral face recognition systems using images collected across the VIS and NIR spectrum can counter the ill-effects of illumination variation by standardising both sets of images. A novel preprocessing technique is proposed, which attempts the transformation of faces across both modalities to a feature space with enhanced correlation. Direct matching across the modalities is not possible due to the inherent spectral differences between NIR and VIS face images. Compared to a VIS light source, NIR radiation has a greater penetrative depth when incident on human skin. This fact, in addition to the greater number of scattering interactions within the skin by rays from the NIR spectrum can alter the morphology of the human face enough to disable a direct match with the corresponding VIS face. Several ways to bridge the gap between NIR-VIS faces have been proposed previously. Mostly of a data-driven approach, these techniques include standardised photometric normalisation techniques and subspace projections. A generative approach driven by a true physical model has not been investigated till now. In this thesis, it is proposed that a large proportion of the scattering interactions present in the NIR spectrum can be accounted for using a model for subsurface scattering. A novel subsurface scattering inversion (SSI) algorithm is developed that implements an inversion approach based on translucent surface rendering by the computer graphics field, whereby the reversal of the first order effects of subsurface scattering is attempted. The SSI algorithm is then evaluated against several preprocessing techniques, and using various permutations of feature extraction and subspace projection algorithms. The results of this evaluation show an improvement in cross spectral face recognition performance using SSI over existing Retinex-based approaches. The top performing combination of an existing photometric normalisation technique, Sequential Chain, is seen to be the best performing with a Rank 1 recognition rate of 92. 5%. In addition, the improvement in performance using non-linear projection models shows an element of non-linearity exists in the relationship between NIR and VIS

Face Video Competition

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-01793-3_73Person recognition using facial features, e.g., mug-shot images, has long been used in identity documents. However, due to the widespread use of web-cams and mobile devices embedded with a camera, it is now possible to realise facial video recognition, rather than resorting to just still images. In fact, facial video recognition offers many advantages over still image recognition; these include the potential of boosting the system accuracy and deterring spoof attacks. This paper presents the first known benchmarking effort of person identity verification using facial video data. The evaluation involves 18 systems submitted by seven academic institutes.The work of NPoh is supported by the advanced researcher fellowship PA0022121477of the Swiss NSF; NPoh, CHC and JK by the EU-funded Mobio project grant IST-214324; NPC and HF by the EPSRC grants EP/D056942 and EP/D054818; VS andNP by the Slovenian national research program P2-0250(C) Metrology and Biomet-ric System, the COST Action 2101 and FP7-217762 HIDE; and, AAS by the Dutch BRICKS/BSIK project.Poh, N.; Chan, C.; Kittler, J.; Marcel, S.; Mc Cool, C.; Rua, E.; Alba Castro, J.... (2009). Face Video Competition. En Advances in Biometrics: Third International Conference, ICB 2009, Alghero, Italy, June 2-5, 2009. Proceedings. 715-724. https://doi.org/10.1007/978-3-642-01793-3_73S715724Messer, K., Kittler, J., Sadeghi, M., Hamouz, M., Kostyn, A., Marcel, S., Bengio, S., Cardinaux, F., Sanderson, C., Poh, N., Rodriguez, Y., Kryszczuk, K., Czyz, J., Vandendorpe, L., Ng, J., Cheung, H., Tang, B.: Face authentication competition on the BANCA database. In: Zhang, D., Jain, A.K. (eds.) ICBA 2004. LNCS, vol. 3072, pp. 8–15. Springer, Heidelberg (2004)Messer, K., Kittler, J., Sadeghi, M., Hamouz, M., Kostin, A., Cardinaux, F., Marcel, S., Bengio, S., Sanderson, C., Poh, N., Rodriguez, Y., Czyz, J., Vandendorpe, L., McCool, C., Lowther, S., Sridharan, S., Chandran, V., Palacios, R.P., Vidal, E., Bai, L., Shen, L.-L., Wang, Y., Yueh-Hsuan, C., Liu, H.-C., Hung, Y.-P., Heinrichs, A., Muller, M., Tewes, A., vd Malsburg, C., Wurtz, R., Wang, Z., Xue, F., Ma, Y., Yang, Q., Fang, C., Ding, X., Lucey, S., Goss, R., Schneiderman, H.: Face authentication test on the BANCA database. In: Int’l. Conf. Pattern Recognition (ICPR), vol. 4, pp. 523–532 (2004)Phillips, P.J., Flynn, P.J., Scruggs, T., Bowyer, K.W., Chang, J., Hoffman, K., Marques, J., Min, J., Worek, W.: Overview of the Face Recognition Grand Challenge. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 947–954 (2005)Bailly-Baillière, E., Bengio, S., Bimbot, F., Hamouz, M., Kittler, J., Marithoz, J., Matas, J., Messer, K., Popovici, V., Porée, F., Ruiz, B., Thiran, J.-P.: The BANCA Database and Evaluation Protocol. In: Kittler, J., Nixon, M.S. (eds.) AVBPA 2003. LNCS, vol. 2688. Springer, Heidelberg (2003)Turk, M., Pentland, A.: Eigenfaces for Recognition. Journal of Cognitive Neuroscience 3(1), 71–86 (1991)Martin, A., Doddington, G., Kamm, T., Ordowsk, M., Przybocki, M.: The DET Curve in Assessment of Detection Task Performance. In: Proc. Eurospeech 1997, Rhodes, pp. 1895–1898 (1997)Bengio, S., Marithoz, J.: The Expected Performance Curve: a New Assessment Measure for Person Authentication. In: The Speaker and Language Recognition Workshop (Odyssey), Toledo, pp. 279–284 (2004)Poh, N., Bengio, S.: Database, Protocol and Tools for Evaluating Score-Level Fusion Algorithms in Biometric Authentication. Pattern Recognition 39(2), 223–233 (2005)Martin, A., Przybocki, M., Campbell, J.P.: The NIST Speaker Recognition Evaluation Program, ch. 8. Springer, Heidelberg (2005

Robust face recognition by an albedo based 3D morphable model

Large pose and illumination variations are very challenging for face recognition. The 3D Morphable Model (3DMM) approach is one of the effective methods for pose and illumination invariant face recognition. However, it is very difficult for the 3DMM to recover the illumination of the 2D input image because the ratio of the albedo and illumination contributions in a pixel intensity is ambiguous. Unlike the traditional idea of separating the albedo and illumination contributions using a 3DMM, we propose a novel Albedo Based 3D Morphable Model (AB3DMM), which removes the illumination component from the images using illumination normalisation in a preprocessing step. A comparative study of different illumination normalisation methods for this step is conducted on PIE and Multi-PIE databases. The results show that overall performance of our method outperforms state-of-the-art methods

Luminosity Distributions within Rich Clusters - II: Demonstration and Verification via Simulation

We present detailed simulations of long exposure CCD images. The simulations are used to explore the validity of the statistical method for reconstructing the luminosity distribution of galaxies within a rich cluster i.e. by the subtraction of field number-counts from those of a sight-line through the cluster. In particular we use the simulations to establish the reliability of our observational data presented in Paper 3. Based on our intended CCD field-of-view (6.5 by 6.5 arcmins) and a 1-sigma detection limit of 26 mags per sq arcsecond, we conclude that the luminosity distribution can be robustly determined over a wide range of absolute magnitude (-23 < M_{R} < -16) provided: (a) the cluster has an Abell richness 1.5 or greater, (b) the cluster's redshift lies in the range 0.1 < z < 0.3, (c) the seeing is better than FWHM 1.25'' and (d) the photometric zero points are accurate to within Delta m = \pm 0.12. If these conditions are not met then the recovered luminosity distribution is unreliable and potentially grossly miss-leading. Finally although the method clearly has limitations, within these limitations the technique represents an extremely promising probe of galaxy evolution and environmental dependencies.Comment: 24 pages, 8 figures accepted for publication in MNRAS also available from http://star-www.st-and.ac.uk/~spd3/bib.htm

Image quality-based adaptive illumination normalisation for face recognition

Automatic face recognition is a challenging task due to intra-class variations. Changes in lighting conditions during enrolment and identification stages contribute significantly to these intra-class variations. A common approach to address the effects such of varying conditions is to pre-process the biometric samples in order normalise intra-class variations. Histogram equalisation is a widely used illumination normalisation technique in face recognition. However, a recent study has shown that applying histogram equalisation on well-lit face images could lead to a decrease in recognition accuracy. This paper presents a dynamic approach to illumination normalisation, based on face image quality. The quality of a given face image is measured in terms of its luminance distortion by comparing this image against a known reference face image. Histogram equalisation is applied to a probe image if its luminance distortion is higher than a predefined threshold. We tested the proposed adaptive illumination normalisation method on the widely used Extended Yale Face Database B. Identification results demonstrate that our adaptive normalisation produces better identification accuracy compared to the conventional approach where every image is normalised, irrespective of the lighting condition they were acquired

Illumination and Expression Invariant Face Recognition: Toward Sample Quality-based Adaptive Fusion

The performance of face recognition schemes is adversely affected as a result of significant to moderate variation in illumination, pose, and facial expressions. Most existing approaches to face recognition tend to deal with one of these problems by controlling the other conditions. Beside strong efficiency requirements, face recognition systems on constrained mobile devices and PDA's are expected to be robust against all variations in recording conditions that arise naturally as a result of the way such devices are used. Wavelet-based face recognition schemes have been shown to meet well the efficiency requirements. Wavelet transforms decompose face images into different frequency subbands at different scales, each giving rise to different representation of the face, and thereby providing the ingredients for a multi-stream approach to face recognition which stand a real chance of achieving acceptable level of robustness. This paper is concerned with the best fusion strategy for a multi-stream face recognition scheme. By investigating the robustness of different wavelet subbands against variation in lighting conditions and expressions, we shall demonstrate the shortcomings of current non-adaptive fusion strategies and argue for the need to develop an image quality based, intelligent, dynamic fusion strategy

The curious case of the companion: evidence for cold accretion onto a dwarf satellite near the isolated elliptical NGC 7796

The isolated elliptical (IE) NGC 7796 is accompanied by an interesting early-type dwarf galaxy, named NGC7796-DW1. It exhibits a tidal tail, very boxy isophotes, and multiple nuclei or regions (A, B, and C) that are bluer than the bulk population of the galaxy, indicating a younger age. These properties are suggestive of a dwarf-dwarf merger remnant. We use the Multi-Unit Spectroscopic Explorer (MUSE) at the VLT to investigate NGC 7796-DW1. We extract characteristic spectra to which we apply the STARLIGHT population synthesis software to obtain ages and metallicities of the various population components of the galaxy. The galaxy's main body is old and metal-poor. A surprising result is the extended line emission in the galaxy, forming a ring-like structure with a projected diameter of 2.2 kpc. The line ratios fall into the regime of HII-regions, although OB-stellar populations cannot be identified by spectral signatures. Nucleus A is a relatively old (7 Gyr or older) and metal-poor super star cluster, most probably the nucleus of the dwarf, now displaced. The star-forming regions B and C show younger and distinctly more metal-rich components. The emission line ratios of regions B and C indicate an almost solar oxygen abundance, if compared with radiation models of HII regions. NGC7796-DW1 occupies a particular role in the group of transition-type galaxies with respect to its origin and current evolutionary state, being the companion of an IE. The dwarf-dwarf merger scenario is excluded because of the missing metal-rich merger component. A viable alternative is gas accretion from a reservoir of cold, metal-rich gas. NGC7796 has to provide this gas within its X-ray bright halo. As illustrated by NGC7796-DW1, cold accretion may be a general solution to the problem of extended star formation histories in transition dwarf galaxies. (abridged)Comment: comments: 13 pages, 8 figures, accepted for publication in Astronomy & Astrophysic

X-ray spectral modelling of the AGN obscuring region in the CDFS: Bayesian model selection and catalogue

AGN are known to have complex X-ray spectra that depend on both the properties of the accreting SMBH (e.g. mass, accretion rate) and the distribution of obscuring material in its vicinity ("torus"). Often however, simple and even unphysical models are adopted to represent the X-ray spectra of AGN. In the case of blank field surveys in particular, this should have an impact on e.g. the determination of the AGN luminosity function, the inferred accretion history of the Universe and also on our understanding of the relation between AGN and their host galaxies. We develop a Bayesian framework for model comparison and parameter estimation of X-ray spectra. We take into account uncertainties associated with X-ray data and photometric redshifts. We also demonstrate how Bayesian model comparison can be used to select among ten different physically motivated X-ray spectral models the one that provides a better representation of the observations. Despite the use of low-count spectra, our methodology is able to draw strong inferences on the geometry of the torus. For a sample of 350 AGN in the 4 Ms Chandra Deep Field South field, our analysis identifies four components needed to represent the diversity of the observed X-ray spectra: (abridged). Simpler models are ruled out with decisive evidence in favour of a geometrically extended structure with significant Compton scattering. Regarding the geometry of the obscurer, there is strong evidence against both a completely closed or entirely open toroidal geometry, in favour of an intermediate case. The additional Compton reflection required by data over that predicted by toroidal geometry models, may be a sign of a density gradient in the torus or reflection off the accretion disk. Finally, we release a catalogue with estimated parameters such as the accretion luminosity in the 2-10 keV band and the column density, $N_{H}$, of the obscurer.Comment: 28 pages, 18 figures, catalogue available from https://www.mpe.mpg.de/~jbuchner/agn_torus/analysis/cdfs4Ms_cat/, software available from https://github.com/JohannesBuchner/BX