Digital processing of diffusion-tensor images of avascular tissues

Diffusion is the process that leads to the mixing of substances as a result of spontaneous and random thermal motion of individual atoms and molecules. It was first detected by the English botanist Robert Brown in 1827, and the phenomenon became known as ‘Brownian motion’. More specifically, the motion observed by Brown was translational diffusion – thermal motion resulting in random variations of the position of a molecule. This type of motion was given a correct theoretical interpretation in 1905 by Albert Einstein, who derived the relationship between temperature, the viscosity of the medium, the size of the diffusing molecule, and its diffusion coefficient. It is translational diffusion that is indirectly observed in MR diffusion-tensor imaging (DTI). The relationship obtained by Einstein provides the physical basis for using translational diffusion to probe the microscopic environment surrounding the molecule.

Person-independent facial expression detection using constrained local models

In automatic facial expression detection, very accurate registration is desired which can be achieved via a deformable model approach where a dense mesh of 60-70 points on the face is used, such as an active appearance model (AAM). However, for applications where manually labeling frames is prohibitive, AAMs do not work well as they do not generalize well to unseen subjects. As such, a more coarse approach is taken for person-independent facial expression detection, where just a couple of key features (such as face and eyes) are tracked using a Viola-Jones type approach. The tracked image is normally post-processed to encode for shift and illumination invariance using a linear bank of filters. Recently, it was shown that this preprocessing step is of no benefit when close to ideal registration has been obtained. In this paper, we present a system based on the Constrained Local Model (CLM) which is a generic or person-independent face alignment algorithm which gains high accuracy. We show these results against the LBP feature extraction on the CK+ and GEMEP datasets.

Automatically detecting pain in video through facial action units

In a clinical setting, pain is reported either through patient self-report or via an observer. Such measures are problematic as they are: 1) subjective, and 2) give no specific timing information. Coding pain as a series of facial action units (AUs) can avoid these issues as it can be used to gain an objective measure of pain on a frame-by-frame basis. Using video data from patients with shoulder injuries, in this paper, we describe an active appearance model (AAM)-based system that can automatically detect the frames in video in which a patient is in pain. This pain data set highlights the many challenges associated with spontaneous emotion detection, particularly that of expression and head movement due to the patient's reaction to pain. In this paper, we show that the AAM can deal with these movements and can achieve significant improvements in both the AU and pain detection performance compared to the current-state-of-the-art approaches which utilize similarity-normalized appearance features only.

Unpacking Japan's 21st century "National Conversation" : images of the future beyond the iron cage of the "Catch Up" model

How does the image of the future operate upon history, and upon national and individual identities? To what extent are possible futures colonized by the image? What are the un-said futurecratic discourses that underlie the image of the future? Such questions inspired the examination of Japan’s futures images in this thesis. The theoretical point of departure for this examination is Polak’s (1973) seminal research into the theory of the ‘image of the future’ and seven contemporary Japanese texts which offer various alternative images for Japan’s futures, selected as representative of a ‘national conversation’ about the futures of that nation. These seven images of the future are: 1. Report of the Prime Minister’s Commission on Japan’s Goals in the 21st Century—The Frontier Within: Individual Empowerment and Better Governance in the New Millennium, compiled by a committee headed by Japan’s preeminent Jungian psychologist Kawai Hayao (1928-2007); 2. Slow Is Beautiful—a publication by Tsuji Shinichi, in which he re-images Japan as a culture represented by the metaphor of the sloth, concerned with slow and quality-oriented livingry as a preferred image of the future to Japan’s current post-bubble cult of speed and economic efficiency; 3. MuRatopia is an image of the future in the form of a microcosmic prototype community and on-going project based on the historically significant island of Awaji, and established by Japanese economist and futures thinker Yamaguchi Kaoru; 4. F.U.C.K, I Love Japan, by author Tanja Yujiro provides this seven text image of the future line-up with a youth oriented sub-culture perspective on that nation’s futures; 5. IMAGINATION / CREATION—a compilation of round table discussions about Japan’s futures seen from the point of view of Japan’s creative vanguard; 6. Visionary People in a Visionless Country: 21 Earth Connecting Human Stories is a collection of twenty one essays compiled by Denmark born Tokyo resident Peter David Pedersen; and, 7. EXODUS to the Land of Hope, authored by Murakami Ryu, one of Japan’s most prolific and influential writers, this novel suggests a future scenario portraying a massive exodus of Japan’s youth, who, literate with state-of-the-art information and communication technologies (ICTs) move en masse to Japan’s northern island of Hokkaido to launch a cyber-revolution from the peripheries. The thesis employs a Futures Triangle Analysis (FTA) as the macro organizing framework and as such examines both pushes of the present and weights from the past before moving to focus on the pulls to the future represented by the seven texts mentioned above. Inayatullah’s (1999) Causal Layered Analysis (CLA) is the analytical framework used in examining the texts. Poststructuralist concepts derived primarily from the work of Michel Foucault are a particular (but not exclusive) reference point for the analytical approach it encompasses. The research questions which reflect the triangulated analytic matrix are: 1. What are the pushes—in terms of current trends—that are affecting Japan’s futures? 2. What are the historical and cultural weights that influence Japan’s futures? 3. What are the emerging transformative Japanese images of the future discourses, as embodied in actual texts, and what potential do they offer for transformative change in Japan? Research questions one and two are discussed in Chapter five and research question three is discussed in Chapter six. The first two research questions should be considered preliminary. The weights outlined in Chapter five indicate that the forces working against change in Japan are formidable, structurally deep-rooted, wide-spread, and under-recognized as change-adverse. Findings and analyses of the push dimension reveal strong forces towards a potentially very different type of Japan. However it is the seven contemporary Japanese images of the future, from which there is hope for transformative potential, which form the analytical heart of the thesis. In analyzing these texts the thesis establishes the richness of Japan’s images of the future and, as such, demonstrates the robustness of Japan’s stance vis-à-vis the problem of a perceived map-less and model-less future for Japan. Frontier is a useful image of the future, whose hybrid textuality, consisting of government, business, academia, and creative minority perspectives, demonstrates the earnestness of Japan’s leaders in favour of the creation of innovative futures for that nation. Slow is powerful in its aim to reconceptualize Japan’s philosophies of temporality, and build a new kind of nation founded on the principles of a human-oriented and expanded vision of economy based around the core metaphor of slowness culture. However its viability in Japan, with its post-Meiji historical pushes to an increasingly speed-obsessed social construction of reality, could render it impotent. MuRatopia is compelling in its creative hybridity indicative of an advanced IT society, set in a modern day utopian space based upon principles of a high communicative social paradigm, and sustainability. IMAGINATION / CREATION is less the plan than the platform for a new discussion on Japan’s transformation from an econo-centric social framework to a new Creative Age. It accords with emerging discourses from the Creative Industries, which would re-conceive of Japan as a leading maker of meaning, rather than as the so-called guzu, a term referred to in the book meaning ‘laggard’. In total, Love Japan is still the most idiosyncratic of all the images of the future discussed. Its communication style, which appeals to Japan’s youth cohort, establishes it as a potentially formidable change agent in a competitive market of futures images. Visionary People is a compelling image for its revolutionary and subversive stance against Japan’s vision-less political leadership, showing that it is the people, not the futures-making elite or aristocracy who must take the lead and create a new vanguard for the nation. Finally, Murakami’s Exodus cannot be ruled out as a compelling image of the future. Sharing the appeal of Tanja’s Love Japan to an increasingly disenfranchised youth, Exodus portrays a near-term future that is achievable in the here and now, by Japan’s teenagers, using information and communications technologies (ICTs) to subvert leadership, and create utopianist communities based on alternative social principles. The principal contribution from this investigation in terms of theory belongs to that of developing the Japanese image of the future. In this respect, the literature reviews represent a significant compilation, specifically about Japanese futures thinking, the Japanese image of the future, and the Japanese utopia. Though not exhaustive, this compilation will hopefully serve as a useful starting point for future research, not only for the Japanese image of the future, but also for all image of the future research. Many of the sources are in Japanese and their English summations are an added reason to respect this achievement. Secondly, the seven images of the future analysed in Chapter six represent the first time that Japanese image of the future texts have been systematically organized and analysed. Their translation from Japanese to English can be claimed as a significant secondary contribution. What is more, they have been analysed according to current futures methodologies that reveal a layeredness, depth, and overall richness existing in Japanese futures images. Revealing this image-richness has been one of the most significant findings of this investigation, suggesting that there is fertile research to be found from this still under-explored field, whose implications go beyond domestic Japanese concerns, and may offer fertile material for futures thinkers and researchers, Japanologists, social planners, and policy makers.

Comparison of standard image segmentation methods for segmentation of brain tumors from 2D MR images

In the analysis of medical images for computer-aided diagnosis and therapy, segmentation is often required as a preliminary step. Medical image segmentation is a complex and challenging task due to the complex nature of the images. The brain has a particularly complicated structure and its precise segmentation is very important for detecting tumors, edema, and necrotic tissues in order to prescribe appropriate therapy. Magnetic Resonance Imaging is an important diagnostic imaging technique utilized for early detection of abnormal changes in tissues and organs. It possesses good contrast resolution for different tissues and is, thus, preferred over Computerized Tomography for brain study. Therefore, the majority of research in medical image segmentation concerns MR images. As the core juncture of this research a set of MR images have been segmented using standard image segmentation techniques to isolate a brain tumor from the other regions of the brain. Subsequently the resultant images from the different segmentation techniques were compared with each other and analyzed by professional radiologists to find the segmentation technique which is the most accurate. Experimental results show that the Otsu’s thresholding method is the most suitable image segmentation method to segment a brain tumor from a Magnetic Resonance Image.

Shanghai : images of modernity

This chapter profiles China's biggest city and economic powerhouse, Shanghai. The authors examine the city’s use of culture to position itself as a global city and how a particular narrative of the city has informed western commentators and Shanghai policy makers. They also analyze the development of an arts and cultural infrastructure and the parallel separation of art and entertainment, with contemporary art as an unexpected challenge, but one the city successfully negotiated. They looks at the marketisation of culture and the context in which this takes place, tracing the connections between market reforms in culture and those in the wider economy. The authors are convinced that the half-formed or distorted use of western concepts like creative industries or creative clusters, rather than indicating a duplicity or an incomplete modernity actually highlight some of the complicities of canonical cultural policy.

Improving the performance of facial expression recognition using dynamic, subtle and regional features

Human facial expression is a complex process characterized of dynamic, subtle and regional emotional features. State-of-the-art approaches on facial expression recognition (FER) have not fully utilized this kind of features to improve the recognition performance. This paper proposes an approach to overcome this limitation using patch-based ‘salient’ Gabor features. A set of 3D patches are extracted to represent the subtle and regional features, and then inputted into patch matching operations for capturing the dynamic features. Experimental results show a significant performance improvement of the proposed approach due to the use of the dynamic features. Performance comparison with pervious work also confirms that the proposed approach achieves the highest CRR reported to date on the JAFFE database and a top-level performance on the Cohn-Kanade (CK) database.

Geometry vs appearance for discriminating between posed and spontaneous emotions

Spontaneous facial expressions differ from posed ones in appearance, timing and accompanying head movements. Still images cannot provide timing or head movement information directly. However, indirectly the distances between key points on a face extracted from a still image using active shape models can capture some movement and pose changes. This information is superposed on information about non-rigid facial movement that is also part of the expression. Does geometric information improve the discrimination between spontaneous and posed facial expressions arising from discrete emotions? We investigate the performance of a machine vision system for discrimination between posed and spontaneous versions of six basic emotions that uses SIFT appearance based features and FAP geometric features. Experimental results on the NVIE database demonstrate that fusion of geometric information leads only to marginal improvement over appearance features. Using fusion features, surprise is the easiest emotion (83.4% accuracy) to be distinguished, while disgust is the most difficult (76.1%). Our results find different important facial regions between discriminating posed versus spontaneous version of one emotion and classifying the same emotion versus other emotions. The distribution of the selected SIFT features shows that mouth is more important for sadness, while nose is more important for surprise, however, both the nose and mouth are important for disgust, fear, and happiness. Eyebrows, eyes, nose and mouth are important for anger.

Evaluation of texture and geometry for dimensional facial expression recognition

Facial expression recognition (FER) algorithms mainly focus on classification into a small discrete set of emotions or representation of emotions using facial action units (AUs). Dimensional representation of emotions as continuous values in an arousal-valence space is relatively less investigated. It is not fully known whether fusion of geometric and texture features will result in better dimensional representation of spontaneous emotions. Moreover, the performance of many previously proposed approaches to dimensional representation has not been evaluated thoroughly on publicly available databases. To address these limitations, this paper presents an evaluation framework for dimensional representation of spontaneous facial expressions using texture and geometric features. SIFT, Gabor and LBP features are extracted around facial fiducial points and fused with FAP distance features. The CFS algorithm is adopted for discriminative texture feature selection. Experimental results evaluated on the publicly accessible NVIE database demonstrate that fusion of texture and geometry does not lead to a much better performance than using texture alone, but does result in a significant performance improvement over geometry alone. LBP features perform the best when fused with geometric features. Distributions of arousal and valence for different emotions obtained via the feature extraction process are compared with those obtained from subjective ground truth values assigned by viewers. Predicted valence is found to have a more similar distribution to ground truth than arousal in terms of covariance or Bhattacharya distance, but it shows a greater distance between the means.

Position, rotation, and scale invariant recognition of images using higher-order spectra

A new approach to recognition of images using invariant features based on higher-order spectra is presented. Higher-order spectra are translation invariant because translation produces linear phase shifts which cancel. Scale and amplification invariance are satisfied by the phase of the integral of a higher-order spectrum along a radial line in higher-order frequency space because the contour of integration maps onto itself and both the real and imaginary parts are affected equally by the transformation. Rotation invariance is introduced by deriving invariants from the Radon transform of the image and using the cyclic-shift invariance property of the discrete Fourier transform magnitude. Results on synthetic and actual images show isolated, compact clusters in feature space and high classification accuracies

Face recognition using fractal codes

In this paper we propose a new method for face recognition using fractal codes. Fractal codes represent local contractive, affine transformations which when iteratively applied to range-domain pairs in an arbitrary initial image result in a fixed point close to a given image. The transformation parameters such as brightness offset, contrast factor, orientation and the address of the corresponding domain for each range are used directly as features in our method. Features of an unknown face image are compared with those pre-computed for images in a database. There is no need to iterate, use fractal neighbor distances or fractal dimensions for comparison in the proposed method. This method is robust to scale change, frame size change and rotations as well as to some noise, facial expressions and blur distortion in the image