Assessing human skin color from uncalibrated images

Images of a scene captured with multiple cameras will have different color values due to variations in color rendering across devices. We present a method to accurately retrieve color information from uncalibrated images taken under uncontrolled lighting conditions with an unknown device and no access to raw data, but with a limited number of reference colors in the scene. The method is used to assess skin tones. A subject is imaged with the calibration target in the scene. This target is extracted and its color values are used to compute a color correction transform that is applied to the entire image. We establish that the best mapping is done using a target consisting of skin colored patches representing the whole range of human skin colors. We show that color information extracted from images is well correlated with color data derived from spectral measurements of skin. We also show that skin color can be consistently measured across cameras with different color rendering and resolutions ranging from 0.1 Mpixels to 4.0 Mpixels

Algorithms for the enhancement of dynamic range and colour constancy of digital images & video

One of the main objectives in digital imaging is to mimic the capabilities of the human eye, and perhaps, go beyond in certain aspects. However, the human visual system is so versatile, complex, and only partially understood that no up-to-date imaging technology has been able to accurately reproduce the capabilities of the it. The extraordinary capabilities of the human eye have become a crucial shortcoming in digital imaging, since digital photography, video recording, and computer vision applications have continued to demand more realistic and accurate imaging reproduction and analytic capabilities. Over decades, researchers have tried to solve the colour constancy problem, as well as extending the dynamic range of digital imaging devices by proposing a number of algorithms and instrumentation approaches. Nevertheless, no unique solution has been identified; this is partially due to the wide range of computer vision applications that require colour constancy and high dynamic range imaging, and the complexity of the human visual system to achieve effective colour constancy and dynamic range capabilities. The aim of the research presented in this thesis is to enhance the overall image quality within an image signal processor of digital cameras by achieving colour constancy and extending dynamic range capabilities. This is achieved by developing a set of advanced image-processing algorithms that are robust to a number of practical challenges and feasible to be implemented within an image signal processor used in consumer electronics imaging devises. The experiments conducted in this research show that the proposed algorithms supersede state-of-the-art methods in the fields of dynamic range and colour constancy. Moreover, this unique set of image processing algorithms show that if they are used within an image signal processor, they enable digital camera devices to mimic the human visual system s dynamic range and colour constancy capabilities; the ultimate goal of any state-of-the-art technique, or commercial imaging device

Design considerations for a marker-free visual-based interfacing device for telco operation

Abstract: The parts of the system in the telecommunication environment that is used by technicians are sometimes completely menu driven. The interfaces to these parts can be made much simpler. Visual-based interfacing is a relatively new field of interest with advancements being made toward marker free human input tracking..

A low power colour-based skin detectors for smart environments

We describe an embedded optical system detecting human skin under a wide range of illuminant conditions. Our attention to such a system is justified by the many applications for which skin detection is needed, e.g. automatic people monitoring and tracking for security reasons or hand gesture recognition for fast and natural human-machine interaction. The presented system consists of a low power RGB sensor connected to an energy efficient microcontroller. The RGB sensor acquires the RGB signal from a region in front of it over a wide dynamic range, converts it in the rg chromaticity space directly on chip and delivers the processed data to the microcontroller. This latter classifies the input signal as skin or non-skin, testing its membership to a skin locus, i.e. to a compact set representing the chromaticities of the human skin tones acquired under several illuminant conditions. The system architecture distributes the computational load of skin detection on both hardware and software, providing a reliable skin detection with a limited energy consumption. This makes the system suitable to be used in smart environments, where energy efficiency is highly desired in order to keep the sensors always ready to receive, process and transmit data without affecting the performance

A Marker-free Visual Based Interfacing Device for Menu Driven Systems

In this paper we propose a marker-free visual based interface device to be used with menu driven systems. This system, called HandsFree, uses the Graphics Processing Unit (GPU) together with Shader technology to perform the image processing..

Modelling Colour Appearance: Applications in Skin Image Perception

Humans are trichromatic, and yet their perception of colours is rich and complex. The research presented in this thesis explores the process of colour appearance of uniform patches and natural polychromatic stimuli. This is done through the measurement and analysis of the achromatic locus (Chapter 2), modelling of chromatic adaptation in a large dataset of unique hues settings (Chapter 3), and measurement of thresholds for uniform and polychromatic stimuli derived from simulated skin images (Chapter 4). Chapter 2 proposes a novel navigation scheme based on unique hues for traversing colour space. The results show that when colour adjustments are made using this novel scheme, the variability of achromatic settings made by observers is reduced compared to the classical method of making colour adjustments along the cardinal axes of the CIELUV colour space. This result holds across the tested luminance levels (5,20,50 cd/m^2) in each of the three tested ambient illumination conditions – dark, simulated daylight and cool white fluorescent lighting. The analysis also shows that the direction of maximum variance of the achromatic settings lies along the daylight locus. Chapter 3 evaluates models of chromatic adaptation by using unique hues settings measured under different ambient illumination conditions. It is shown that a simple diagonal model in cone excitation space is the most efficient in terms of the trade-off between accuracy and degrees of freedom. It is also found that diagonal and linear models show similar performances, reiterating their theoretical equivalence. Performances of these diagonalisable models are found to be worse for UR and UG unique hue planes compared to UY and UB planes. Chapter 4 presents a set of three experiments reporting estimations of perceptual thresholds for polychromatic and uniform stimuli in a 3-D chromaticity-luminance colour space. The first experiment reports thresholds for simulated skin images and uniform stimuli of the corresponding mean CIELAB colour. The second and third experiments investigate the effect of ambient illumination and the location of the stimuli in colour space. The thresholds for the polychromatic stimuli are found to be consistently higher than those for the uniform patches, for both the chromatic, and the luminance projections. The area of the chromaticity ellipses shows a gradual increase with distance from the illuminant chromaticity. The orientations of these ellipses for simulated skin are found to align with the vector joining the mean patch chromaticity and the illuminant chromaticity

Model facial colour appearance and facial attractiveness for human complexions

Human facial complexion has been a subject of great interest in many areas of science and technology including dermatology, cosmetology, computer graphics, and computer vision. Facial colour appearance conveys vital personal information and influences social interactions and mate choices as contributing factors to perceived beauty, health, and age. How various colour characteristics affect facial preference and whether there are cultural differences are not fully understood. On the other hand, facial colour appearance cannot be simply quantified by colour measurement. Facial colour perception is distinctive. The perceptual aspects of facial colour appearance haven’t been precisely investigated. The present study aims to better understand the human colour perception of facial complexions. Psychophysical experiments were carried out to assess facial colour preference and facial colour appearance, respectively. A set of facial images of real human faces were used and the colour was rigorously controlled in those experiments so that the facial colour appearance could be evaluated based on the realistic skin models. Experiments on colour preference provided a thorough assessment of the relationships between various facial colour characteristics and preference judgements and meanwhile revealed large cultural differences between Caucasian and Chinese populations. A useful and repeatable analytical framework for facial preference modelling was provided. This work contributes to the growing body of research using realistic skin models and highlights the importance of examining various colour cues utilized in facial preference evaluation. Experiments on colour appearance for the first time precisely measured the overall colour perception of facial appearance. New indices WIS, RIS, and YIS were developed to accurately quantify perceived facial whiteness, redness, and yellowness. The perceptual difference between the colour appearance of the face stimuli and the nonface stimuli was discovered. Taken together, the present study shed new light on how our visual system perceives and processes colour information on human faces

Application of Physics-Based Image Formation Models to Change Detection in The Context of Indoor Workplace Video Surveillance

The aim of this thesis is to investigate the application of physics-based image formation models to change detection in the context of indoor workplace video surveillance. First, video surveillance applications are reviewed. Based on this review, a new classification of video surveillance applications is proposed and indoor workplace surveillance is chosen as the target application. A new workplace surveillance modelis then introduced, which relates the needs of workplace surveillance applications, their implications and the capabilities of video surveillance techniques. Furthermore, a set of requirements for workplace surveillance applications are elicited and a videobased workplace system structure is proposed. Change detection is then reviewed, and the suitability of using physics-based image formation models to enhance change detection algorithms is investigated. Two physics-based change detection techniques are developed. The foundations of these techniques are advances of colour constancy techniques which extract physical features from the camera output; this approach is unlike other change detection algorithms which use the camera output directly without considering its physical meaning. The performance of the proposed techniques is measured and compared against the Horprasert algorithm, using objective and computational complexity evaluation methods, where the quality of the change detection is measured using recall and precision measures. The Horprasert algorithm was shown, in an independent study by other researchers, to have the best trade-off between segmentation quality and computational complexity among other state-of-the-art algorithms such as Cavallaro, McKenna and Shen under experimental conditions which covered different lightings and background structures