Colour invariants for machine face recognition

Illumination invariance remains the most researched, yet the most challenging aspect of automatic face recognition. In this paper we investigate the discriminative power of colour-based invariants in the presence of large illumination changes between training and test data, when appearance changes due to cast shadows and non-Lambertian effects are significant. Specifically, there are three main contributions: (i) we employ a more sophisticated photometric model of the camera and show how its parameters can be estimated, (ii) we derive several novel colour-based face invariants, and (iii) on a large database of video sequences we examine and evaluate the largest number of colour-based representations in the literature. Our results suggest that colour invariants do have a substantial discriminative power which may increase the robustness and accuracy of recognition from low resolution images

Estimating the polarization degree of polarimetric images in coherent illumination using maximum likelihood methods

This paper addresses the problem of estimating the polarization degree of polarimetric images in coherent illumination. It has been recently shown that the degree of polarization associated to polarimetric images can be estimated by the method of moments applied to two or four images assuming fully developed speckle. This paper shows that the estimation can also be conducted by using maximum likelihood methods. The maximum likelihood estimators of the polarization degree are derived from the joint distribution of the image intensities. We show that the joint distribution of polarimetric images is a multivariate gamma distribution whose marginals are univariate, bivariate or trivariate gamma distributions. This property is used to derive maximum likelihood estimators of the polarization degree using two, three or four images. The proposed estimators provide better performance that the estimators of moments. These results are illustrated by estimations conducted on synthetic and real images

Review and Comparison of High-Dynamic Range Three-Dimensional Shape Measurement Techniques

In the last decade, a significant number of techniques for three-dimensional (3D) shape measurement have been proposed. There are a large number of measurement demands for metallic workpieces with shiny surfaces in industrial applications; however, such shiny surfaces cannot be directly measured using the conventional structured light method. Therefore, various techniques have been investigated to solve this problem over the last few years. Some reviews summarize the different 3D imaging techniques; however, no comprehensive review exists that provides an insight into high-dynamic range (HDR) 3D shape measurement techniques used for shiny surfaces. We present a survey of recent HDR techniques for the digitization of shiny surfaces and classify and discuss the advantages and drawbacks of different techniques with respect to each other

New 3D scanning techniques for complex scenes

This thesis presents new 3D scanning methods for complex scenes, such as surfaces with fine-scale geometric details, translucent objects, low-albedo objects, glossy objects, scenes with interreflection, and discontinuous scenes. Starting from the observation that specular reflection is a reliable visual cue for surface mesostructure perception, we propose a progressive acquisition system that captures a dense specularity field as the only information for mesostructure reconstruction. Our method can efficiently recover surfaces with fine-scale geometric details from complex real-world objects. Translucent objects pose a difficult problem for traditional optical-based 3D scanning techniques. We analyze and compare two descattering methods, phaseshifting and polarization, and further present several phase-shifting and polarization based methods for high quality 3D scanning of translucent objects. We introduce the concept of modulation based separation, where a high frequency signal is multiplied on top of another signal. The modulated signal inherits the separation properties of the high frequency signal and allows us to remove artifacts due to global illumination. Thismethod can be used for efficient 3D scanning of scenes with significant subsurface scattering and interreflections.Diese Dissertation präsentiert neuartige Verfahren für die 3D-Digitalisierung komplexer Szenen, wie z.B. Oberflächen mit sehr feinen Strukturen, durchscheinende Objekte, Gegenstände mit geringem Albedo, glänzende Objekte, Szenen mit Lichtinterreflektionen und unzusammenhängende Szenen. Ausgehend von der Beobachtung, daß die spekulare Reflektion ein zuverlässiger, visueller Hinweis für die Mesostruktur einer Oberfläche ist, stellen wir ein progressives Meßsystem vor, um Spekularitätsfelder zu messen. Aus diesen Feldern kann anschließend die Mesostruktur rekonstruiert werden. Mit unserer Methode können Oberflächen mit sehr feinen Strukturen von komplexen, realen Objekten effizient aufgenommen werden. Durchscheinende Objekte stellen ein großes Problem für traditionelle, optischbasierte 3D-Rekonstruktionsmethoden dar. Wir analysieren und vergleichen zwei verschiedene Methoden zum Eliminieren von Lichtstreuung (Descattering): Phasenverschiebung und Polarisation. Weiterhin präsentieren wir mehrere hochqualitative 3D-Rekonstruktionsmethoden für durchscheinende Objekte, die auf Phasenverschiebung und Polarisation basieren. Außerdem führen wir das Konzept der modulationsbasierten Signaltrennung ein. Hierzu wird ein hochfrequentes Signal zu einem anderes Signal multipliziert. Das so modulierte Signal erhält damit die separierenden Eigenschaften des hochfrequenten Signals. Dies erlaubt unsMeßartefakte aufgrund von globalen Beleuchtungseffekten zu vermeiden. Dieses Verfahren kann zum effizienten 3DScannen von Szenen mit durchscheinden Objekten und Interreflektionen benutzt werden

Adaptive Fringe Projection and Error-Compensated Calibration for Compact 3D Shape-Measurement Systems

Measurement of the three-dimensional (3-D) shape of an object is needed for both industrial and consumer applications. In industrial applications, compact measurement systems are needed to accomplish certain tasks such as measuring an interior surface in a confined space. In consumer applications, compact measurement systems are also needed for common consumers to conveniently get access to 3D data for a wide range of everyday uses. Fringe-projection techniques have been increasingly used for 3D shape measurement due to the advantage of dense full-field measurement. For a camera-projector measurement system, system geometry (the relative camera-projector position and angle) determine the system compactness. Analysis of the relation of system geometry to measurement accuracy is challenging owing to the effect of the various factors that vary with system geometry on measurement accuracy. It is thus necessary to experimentally determine how measurement accuracy varies with system geometry, in order to determine the most compact design that satisfies a desired measurement accuracy. This has been achieved in a compactness study, in which the measurement accuracy is evaluated at different relative camera-projector positions and angles. Measurement results in the compactness study have shown that there is a tradeoff in loss of accuracy for increased compactness and loss of compactness for increased accuracy. The smallest camera-projector angle (for an industrial system) or the smallest physical distance between the camera and projector (for a consumer system) that satisfies the desired accuracy would provide the most compact design. Several new methods including 1) an improved heterodyne phase-unwrapping method, 2) an adaptive fringe-pattern projection (AFPP) method for surfaces of high variation in reflectivity and illumination, and 3) a pixel-wise adaptive fringe-pattern projection (PWAFPP) method for such surfaces, have been developed in this research to improve measurement accuracy, thus contributing to enable a more compact system design to achieve a desired measurement accuracy. First, the new improved heterodyne phase-unwrapping method detects and compensates for the spike-like errors in absolute phase maps. The method has demonstrated improved projector calibration accuracy from 18.2 to 0.2 pixels, thus ensuring usable camera-projector stereovision system calibration for 3D measurement. Second, the new AFPP method adapts the projector maximum input gray levels (MIGLs) to local surface reflectivity using only two prior fringe-pattern projection and image-capture rounds. The method demonstrated greatly improved 3D measurement accuracy by avoiding image saturation in highly-reflective surface regions while maintaining high intensity modulation of captured fringe patterns across the entire surface with large range in reflectivity. Third, the new PWAFPP method projects a MIGL adapted to the surface reflectivity and illuminance for each pixel. The method has demonstrated a 34% root-mean-square (RMS) error reduction in 3D measurement for pixels that remained saturated after applying the AFPP method. The new method can thus be used to measure surfaces with more complex variation in surface reflectivity