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Abstract The colours of objects perceived by a colour camera are dependent on the illumination conditions. For example, when the prevailing illumination condition does not correspond to the one used in the white balancing of the camera, the object colours can change their appearance due to the lack of colour constancy capabilities. Many methods for colour constancy have been suggested but so far their performance has been inadequate. Faces are common and important objects encountered in many applications. Therefore, this thesis is dedicated to studying face colours and their robust use under real world illumination conditions. The main thesis statement is "knowledge about an object's colour, like skin colour changes under different illumination conditions, can be used to develop more robust techniques against illumination changes". Many face databases exist, and in some cases they contain colour images and even videos. However, from the point of view of this thesis these databases have several limitations: unavailability of spectral data related to image acquisition, undefined illumination conditions of the acquisition, and if illumination change is present it often means only change in illumination direction. To overcome these limitations, two databases, a Physics-Based Face Database and a Face Video Database were created. In addition to the images, the Physics-Based Face Database consists of spectral data part including skin reflectances, channel responsivities of the camera and spectral power distribution of the illumination. The images of faces are taken under four known light sources with different white balancing illumination conditions for over 100 persons. In addition to videos, the Face Video Database has spectral reflectances of skin for selected persons and images taken with the same measurement arrangement as in the Physics-Based Face Database. The images and videos are taken with several cameras. The databases were used to gather information about skin chromaticities and to provide test material. The skin RGB from images were converted to different colour spaces and the result showed that the normalized colour coordinate was among the most usable colour spaces for skin chromaticity modelling. None of the colour spaces could eliminate the colour shifts in chromaticity. The obtained chromaticity constraint can be implemented as an adaptive skin colour modelling part of face tracking algorithms, like histogram backprojection or mean shift. The performances of these adaptive algorithms were superior compared to those using a fixed skin colour model or model adaptation based on spatial pixel selection. Of course, there are cases when the colour cue is not enough alone and use of other cues like motion or edge data would improve the result. It was also demonstrated that the skin colour model can be used to segment faces and the segmentation results depend on the background due to the method used. Also an application for colour correction using principal component analysis and a simplified dichromatic reflection model was shown to improve colour quality of seriously clipped images. The results of tracking, segmentation and colour correction experiments using the collected data validate the thesis statement.

This research presents a novel framework for automatic chroma keying and the optimizations for real-time and stereoscopic 3D processing. It first simulates the process of human perception on isolating foreground elements in a given scene by perceptual analysis, and then predicts foreground colours and alpha map based on the analysis results and the restored clean background plate rather than direct sampling. Besides, an object level depth map is generated through stereo matching on a carefully determined feature map. In addition, three prototypes on different platforms have been implemented according to their hardware capability based on the proposed framework. To achieve real-time performance, the entire procedures are optimized for parallel processing and data paths on the GPU, as well as heterogeneous computing between GPU and CPU. The qualitative comparisons between results generated by the proposed algorithm and other existing algorithms show that the proposed one is able to generate more acceptable alpha maps and foreground colours especially in those regions that contain translucencies and details. And the quantitative evaluations also validate our advantages in both quality and speed.

Yes / Faces convey much information. Interestingly we humans have a remarkable ability of identifying, extracting, and interpreting this information. Recently automatic facial ageing (AFA) has gained popularity due to its numerous applications which include search for missing people, biometrics, and multimedia. The problem of AFA is faced with various challenges, including incomplete training datasets, unrestrained environments, ethnic and gender variations to mention but a few. This work presents a new approach to automatic facial ageing which involves the development of a person specific facial ageing system. A color based Active Appearance Model (AAM) is used to extract facial features. Then, regression is used to model an age estimator. Age synthesis is achieved by computing a solution that minimises the distance from the original face with the use of constrained regression. The model is tested on a challenging database of single image per person. Initial results suggest that plausible images can be rerendered at different ages, automatically using the AAM representation. Using the constrained regressor we are guaranteed to get estimated ages that are exact for an individual at a given age.