Environmentally robust multiple camera tracking

A significant growth of the use of surveillance cameras has arisen from both the availability of low-cost home security and post-September 11th security measures. With such a plethora of surveillance cameras available and already in use, tracking a person or object from one field of view to another accurately is a challenging possibility; recognising the same person at different spatial locations, under different lighting conditions, at different scales and orientations. In order to address these challenges and provide a solution, a review of recent and past literature is provided. The main theme of this research is investigating methods to improve tracking of objects and people in dynamic environments and applying computational techniques to provide solutions to optimise such tracking systems. Image processing techniques are explored and refactored to adapt to currently available single-board computing power. Optimisation methods for speed of computing are investigated, presenting the paradigm of parallel programming during the design of “computationally intense” algorithms. The research also addresses cross-platform software/ server application design. In controlled environments current tracking systems perform well, however, this project explores methods to take multiple camera tracking to a higher level where they can, in real time, robustly cope with: rapid changes in lighting and track objects between indoor and outdoor scenarios at any time of day or in any weather conditions, severe image occlusion, rapid changes in direction, orientation and velocity of the object being tracked and be invariant to image clutter and noise. Thus the outputs are twofold: track a human/object across multiple cameras and ensure the algorithm is fast enough to run in real time on a modern processor. This research explores algorithms to deliver colour illumination invariance, also known as colour constancy. Colour illumination invariance can be applied as a pre-processing step to all cameras in a multi-camera environment. The research also investigates experimental assessment of multi-camera performance, focusing mainly on robustness to environmental changes. There are three main objectives for a tracking algorithm being used in the proposed system. Firstly, the tracking algorithm must accurately detect objects independently of their scale change and rotation. Secondly, the tracking algorithm must accurately detect objects across multiple cameras in different lighting conditions. The third objective for the tracking algorithm is that it must be able to attain a high level of colour constancy. The last objective can be implemented as a pre-processing step to such a tracking algorithm. This research explores the use of the Scale Invariant Feature Transform (SIFT) and the Speeded-Up Robust Features (SURF) algorithm. These algorithms are discussed in detail in the literature review as well as methods for providing colour illumination invariance

NICE : A Computational solution to close the gap from colour perception to colour categorization

The segmentation of visible electromagnetic radiation into chromatic categories by the human visual system has been extensively studied from a perceptual point of view, resulting in several colour appearance models. However, there is currently a void when it comes to relate these results to the physiological mechanisms that are known to shape the pre-cortical and cortical visual pathway. This work intends to begin to fill this void by proposing a new physiologically plausible model of colour categorization based on Neural Isoresponsive Colour Ellipsoids (NICE) in the cone-contrast space defined by the main directions of the visual signals entering the visual cortex. The model was adjusted to fit psychophysical measures that concentrate on the categorical boundaries and are consistent with the ellipsoidal isoresponse surfaces of visual cortical neurons. By revealing the shape of such categorical colour regions, our measures allow for a more precise and parsimonious description, connecting well-known early visual processing mechanisms to the less understood phenomenon of colour categorization. To test the feasibility of our method we applied it to exemplary images and a popular ground-truth chart obtaining labelling results that are better than those of current state-of-the-art algorithms

The asymmetries of colour constancy as determined through illumination discrimination using tuneable LED light sources

PhD ThesisThe light reflected from object surfaces changes with the spectral content of the illumination. Despite these changes, the human visual system tends to keep the colours of surfaces constant, a phenomenon known as colour constancy. Colour constancy is known to be imperfect under many conditions; however, it is unknown whether the underlying mechanisms present in the retina and the cortex are optimised for the illuminations under which they have evolved, namely, natural daylights, or for particular objects. A novel method of measuring colour constancy, by illumination discrimination, is presented and explored. This method, unlike previous methods of measuring colour constancy, allows the testing of multiple, real, illuminations with arbitrary spectral content, through the application of tuneable, multi-channel LED light sources. Data from both real scenes, under real illuminations, and computer simulations are presented which support the hypothesis that the visual system maintains higher levels of colour constancy for daylight illumination changes, and in particular in the “bluer” direction, which are also the changes most frequent in nature. The low-level cone inputs for various experimental scenes are examined which challenge all traditional theories of colour constancy supporting the conclusions that higher-level mechanisms of colour constancy are biased for particular illuminations. Furthermore, real and simulated neutral (grey) surfaces are shown to affect levels of colour constancy. Moreover, the conceptual framework for discussing colour constancy with respect to emergent LED light sources is discussed.EPSR

Adaptive Methods for Color Vision Impaired Users

Color plays a key role in the understanding of the information in computer environments. It happens that about 5% of the world population is affected by color vision deficiency (CVD), also called color blindness. This visual impairment hampers the color perception, ending up by limiting the overall perception that CVD people have about the surrounding environment, no matter it is real or virtual. In fact, a CVD individual may not distinguish between two different colors, what often originates confusion or a biased understanding of the reality, including web environments, whose web pages are plenty of media elements like text, still images, video, sprites, and so on. Aware of the difficulties that color-blind people may face in interpreting colored contents, a significant number of recoloring algorithms have been proposed in the literature with the purpose of improving the visual perception of those people somehow. However, most of those algorithms lack a systematic study of subjective assessment, what undermines their validity, not to say usefulness. Thus, in the sequel of the research work behind this Ph.D. thesis, the central question that needs to be answered is whether recoloring algorithms are of any usefulness and help for colorblind people or not. With this in mind, we conceived a few preliminary recoloring algorithms that were published in conference proceedings elsewhere. Except the algorithm detailed in Chapter 3, these conference algorithms are not described in this thesis, though they have been important to engender those presented here. The first algorithm (Chapter 3) was designed and implemented for people with dichromacy to improve their color perception. The idea is to project the reddish hues onto other hues that are perceived more regularly by dichromat people. The second algorithm (Chapter 4) is also intended for people with dichromacy to improve their perception of color, but its applicability covers the adaptation of text and image, in HTML5- compliant web environments. This enhancement of color contrast of text and imaging in web pages is done while keeping the naturalness of color as much as possible. Also, to the best of our knowledge, this is the first web recoloring approach targeted to dichromat people that takes into consideration both text and image recoloring in an integrated manner. The third algorithm (Chapter 5) primarily focuses on the enhancement of some of the object contours in still images, instead of recoloring the pixels of the regions bounded by such contours. Enhancing contours is particularly suited to increase contrast in images, where we find adjacent regions that are color indistinguishable from dichromat’s point of view. To our best knowledge, this is one of the first algorithms that take advantage of image analysis and processing techniques for region contours. After accurate subjective assessment studies for color-blind people, we concluded that the CVD adaptation methods are useful in general. Nevertheless, each method is not efficient enough to adapt all sorts of images, that is, the adequacy of each method depends on the type of image (photo-images, graphical representations, etc.). Furthermore, we noted that the experience-based perceptual learning of colorblind people throughout their lives determines their visual perception. That is, color adaptation algorithms must satisfy requirements such as color naturalness and consistency, to ensure that dichromat people improve their visual perception without artifacts. On the other hand, CVD adaptation algorithms should be object-oriented, instead of pixel-oriented (as typically done), to select judiciously pixels that should be adapted. This perspective opens an opportunity window for future research in color accessibility in the field of in human-computer interaction (HCI).A cor desempenha um papel fundamental na compreensão da informação em ambientes computacionais. Porém, cerca de 5% da população mundial é afetada pela deficiência de visão de cor (ou Color Vision Deficiency (CVD), do Inglês), correntemente designada por daltonismo. Esta insuficiência visual dificulta a perceção das cores, o que limita a perceção geral que os indivíduos têm sobre o meio, seja real ou virtual. Efetivamente, um indivíduo com CVD vê como iguais cores que são diferentes, o que origina confusão ou uma compreensão distorcida da realidade, assim como dos ambientes web, onde existe uma abundância de conteúdos média coloridos, como texto, imagens fixas e vídeo, entre outros. Com o intuito de mitigar as dificuldades que as pessoas com CVD enfrentam na interpretação de conteúdos coloridos, tem sido proposto na literatura um número significativo de algoritmos de recoloração, que têm como o objetivo melhorar, de alguma forma, a perceção visual de pessoas com CVD. Porém, a maioria desses trabalhos carece de um estudo sistemático de avaliação subjetiva, o que põe em causa a sua validação, se não mesmo a sua utilidade. Assim, a principal questão à qual se pretende responder, como resultado do trabalho de investigação subjacente a esta tese de doutoramento, é se os algoritmos de recoloração têm ou não uma real utilidade, constituindo assim uma ajuda efetiva às pessoas com daltonismo. Tendo em mente esta questão, concebemos alguns algoritmos de recoloração preliminares que foram publicados em atas de conferências. Com exceção do algoritmo descrito no Capítulo 3, esses algoritmos não são descritos nesta tese, não obstante a sua importância na conceção daqueles descritos nesta dissertação. O primeiro algoritmo (Capítulo 3) foi projetado e implementado para pessoas com dicromacia, a fim de melhorar a sua perceção da cor. A ideia consiste em projetar as cores de matiz avermelhada em matizes que são melhor percebidos pelas pessoas com os tipos de daltonismo em causa. O segundo algoritmo (Capítulo 4) também se destina a melhorar a perceção da cor por parte de pessoas com dicromacia, porém a sua aplicabilidade abrange a adaptação de texto e imagem, em ambientes web compatíveis com HTML5. Isto é conseguido através do realce do contraste de cores em blocos de texto e em imagens, em páginas da web, mantendo a naturalidade da cor tanto quanto possível. Além disso, tanto quanto sabemos, esta é a primeira abordagem de recoloração em ambiente web para pessoas com dicromacia, que trata o texto e a imagem de forma integrada. O terceiro algoritmo (Capítulo 5) centra-se principalmente na melhoria de alguns dos contornos de objetos em imagens, em vez de aplicar a recoloração aos pixels das regiões delimitadas por esses contornos. Esta abordagem é particularmente adequada para aumentar o contraste em imagens, quando existem regiões adjacentes que são de cor indistinguível sob a perspetiva dos observadores com dicromacia. Também neste caso, e tanto quanto é do nosso conhecimento, este é um dos primeiros algoritmos em que se recorre a técnicas de análise e processamento de contornos de regiões. Após rigorosos estudos de avaliação subjetiva com pessoas com daltonismo, concluiu-se que os métodos de adaptação CVD são úteis em geral. No entanto, cada método não é suficientemente eficiente para todos os tipo de imagens, isto é, o desempenho de cada método depende do tipo de imagem (fotografias, representações gráficas, etc.). Além disso, notámos que a aprendizagem perceptual baseada na experiência das pessoas daltónicas ao longo de suas vidas é determinante para perceber aquilo que vêem. Isto significa que os algoritmos de adaptação de cor devem satisfazer requisitos tais como a naturalidade e a consistência da cor, de modo a não pôr em causa aquilo que os destinatários consideram razoável ver no mundo real. Por outro lado, a abordagem seguida na adaptação CVD deve ser orientada aos objetos, em vez de ser orientada aos pixéis (como tem sido feito até ao momento), de forma a possibilitar uma seleção mais criteriosa dos pixéis que deverão ser sujeitos ao processo de adaptação. Esta perspectiva abre uma janela de oportunidade para futura investigação em acessibilidade da cor no domínio da interacção humano-computador (HCI)

Synchronising the Senses: The Impact of Embodied Cognition on Communication, Explored in the Domain of Colour

Colour terms divide the visual spectrum into categorical concepts. Since Berlin & Kay’s (1969) cross-cultural study of colour terms, there has been debate about the extent to which these concepts are constrained by innate biases from perceptual hardware and the environment. This study shows that concepts can affect perception in the domain of colour (e.g., reading the word ‘yellow’ causes us to see yellow). An experiment was run in which participants were asked to adjust the font colour of colour terms to appear grey. In fact, participants adjusted the font colour to perceptually oppose the colour the word described (e.g., the word ‘yellow’ was adjusted to be blue). This is interpreted as over-compensating for a perceptual activation caused by the comprehension of the word. These results are used to argue that cross-cultural patterns in colour term systems do not necessarily imply strong innate biases. It is argued that the most efficient way of converging on, maintaining and transferring a conceptual system is for shared categories to re-organise perception. This re-organisation will converge to optimally fit the perceptual and environmental biases. Therefore, an Embodied, Relativist explanation of cross-cultural patterns is supported. Furthermore, if the comprehension of language involves the activation of perceptual representations, then there will be a communicative pressure to reduce perceptual differences between speakers

Language impairment and colour categories

Goldstein (1948) reported multiple cases of failure to categorise colours in patients that he termed amnesic or anomic aphasics. these patients have a particular difficulty in producing perceptual categories in the absence of other aphasic impairments. we hold that neuropsychological evidence supports the view that the task of colour categorisation is logically impossible without labels

The modulation of simultaneous chromatic contrast induction

A coloured background may induce a contrasting colour in a target figure set against it. This effect, known as 'simultaneous chromatic contrast induction', can strongly influence the way in which we perceive colours and may therefore play an important role in our colour perception. Yet in order to support putative roles in phenomena such as colour-constancy, simultaneous contrast effects must be in some way 'regulated', otherwise they would cause objects to change colour when moved from one setting to another. Here we investigate a number of candidate cues that might be expected to influence the strength of simultaneous chromatic contrast. In experiment 1, we investigate the influence of global illumination cues that can indicate whether a colour change is consistent with a change in the illumination over the entire scene, or with a localised change in the background colour. Global illumination changes have already been shown to facilitate simultaneous contrast induction, and we further find that this effect is diminished by increasing the luminance contrast between the elements that make up the scene. Contrary to our expectations, increasing the number of distinct chromaticities in the surround does not have any effect. Finally, we attempt to discover whether this effect occurs at a monocular or a binocular site, by presenting different elements of the stimuli either to the same eye as the target, or to different eyes. Here, our results suggest that the effect is probably binocular. In experiment 2, we investigate how the strength of simultaneous contrast induction changes when textured backgrounds and targets are substituted for the uniformly shaded backgrounds and targets that have been studied in most recent investigations of simultaneous contrast induction. Texture in the background reduces the strength of simultaneous contrast induction for uniform targets. However, texture in targets set against a uniform background strongly inhibits simultaneous contrast induction. When both background and target are textured, simultaneous contrast induction is partially restored suggesting that texture may exert its influence due to segmentation effects. However, another result shows that simultaneous contrast is primarily determined at a local level, arguing against this interpretation of the effect. We do show that the effects of texture are tightly tuned to the cardinal axes, implicating early visual mechanisms in the functioning of simultaneous chromatic contrast effects. In experiment 3, we investigate two other strong segmentation cues: binocular disparity and differential motion between a target and its immediate surround. Our results show that differential motion may facilitate simultaneous contrast induction, strengthening its effects. However the effect is small and is often inconsistent between observers.EThOS - Electronic Theses Online ServicePhysiological SocietyBarbour FoundationRidley Family FundGBUnited Kingdo

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

Visualisation methods for polarimetric imaging

Polarimetric imaging is a technique for measuring the spatial correlations of the aspects of the polarisation of light. Since human vision is essentially unable to detect polarisation, the data obtained from this imaging technique must be converted into the channels of the human visual system in order to visually process the spatial correlations in the data. The technique for converting non-visual data into a visual representation is known as data visualisation. While the techniques for visualising other types of data is well studied, techniques specific for polarimetric imaging are understudied. This research aims to survey the current state of polarimetric imaging visualisation, to analyse the current methods using metrics from visualisation research, to improve on the existing techniques, to test the effectiveness of different methods in terms of user performance, and to develop novel colourmapping methods