Clergy, crusified within the body of Christ - a challenge to pastoral care

M.A. Thesis / University of Pretoria / Department of Practical Theology / Advised by Prof M Masango

Estimating 3D Body Pose Using Uncalibrated Cameras

An approach for estimating 3D body pose from multiple, uncalibrated views is proposed. First, a mapping from image features to 2D body joint locations is computed using a statistical framework that yields a set of several body pose hypotheses. The concept of a "virtual camera" is introduced that makes this mapping invariant to translation, image-plane rotation, and scaling of the input. As a consequence, the calibration matrices (intrinsics) of the virtual cameras can be considered completely known, and their poses are known up to a single angular displacement parameter. Given pose hypotheses obtained in the multiple virtual camera views, the recovery of 3D body pose and camera relative orientations is formulated as a stochastic optimization problem. An Expectation-Maximization algorithm is derived that can obtain the locally most likely (self-consistent) combination of body pose hypotheses. Performance of the approach is evaluated with synthetic sequences as well as real video sequences of human motion.

Specialized Mappings Architecture with Applications to Vision-based Estimation of Articulated Body Pose

A fundamental task of vision systems is to infer the state of the world given some form of visual observations. From a computational perspective, this often involves facing an ill-posed problem; e.g., information is lost via projection of the 3D world into a 2D image. Solution of an ill-posed problem requires additional information, usually provided as a model of the underlying process. It is important that the model be both computationally feasible as well as theoretically well-founded. In this thesis, a probabilistic, nonlinear supervised computational learning model is proposed: the Specialized Mappings Architecture (SMA). The SMA framework is demonstrated in a computer vision system that can estimate the articulated pose parameters of a human body or human hands, given images obtained via one or more uncalibrated cameras. The SMA consists of several specialized forward mapping functions that are estimated automatically from training data, and a possibly known feedback function. Each specialized function maps certain domains of the input space (e.g., image features) onto the output space (e.g., articulated body parameters). A probabilistic model for the architecture is first formalized. Solutions to key algorithmic problems are then derived: simultaneous learning of the specialized domains along with the mapping functions, as well as performing inference given inputs and a feedback function. The SMA employs a variant of the Expectation-Maximization algorithm and approximate inference. The approach allows the use of alternative conditional independence assumptions for learning and inference, which are derived from a forward model and a feedback model. Experimental validation of the proposed approach is conducted in the task of estimating articulated body pose from image silhouettes. Accuracy and stability of the SMA framework is tested using artificial data sets, as well as synthetic and real video sequences of human bodies and hands.

Inferring Body Pose without Tracking Body Parts

A novel approach for estimating articulated body posture and motion from monocular video sequences is proposed. Human pose is defined as the instantaneous two dimensional configuration (i.e., the projection onto the image plane) of a single articulated body in terms of the position of a predetermined set of joints. First, statistical segmentation of the human bodies from the background is performed and low-level visual features are found given the segmented body shape. The goal is to be able to map these, generally low level, visual features to body configurations. The system estimates different mappings, each one with a specific cluster in the visual feature space. Given a set of body motion sequences for training, unsupervised clustering is obtained via the Expectation Maximation algorithm. Then, for each of the clusters, a function is estimated to build the mapping between low-level features to 3D pose. Currently this mapping is modeled by a neural network. Given new visual features, a mapping from each cluster is performed to yield a set of possible poses. From this set, the system selects the most likely pose given the learned probability distribution and the visual feature similarity between hypothesis and input. Performance of the proposed approach is characterized using a new set of known body postures, showing promising results.

Estimating Human Body Pose from a Single Image via the Specialized Mappings Architecture

A non-linear supervised learning architecture, the Specialized Mapping Architecture (SMA) and its application to articulated body pose reconstruction from single monocular images is described. The architecture is formed by a number of specialized mapping functions, each of them with the purpose of mapping certain portions (connected or not) of the input space, and a feedback matching process. A probabilistic model for the architecture is described along with a mechanism for learning its parameters. The learning problem is approached using a maximum likelihood estimation framework; we present Expectation Maximization (EM) algorithms for two different instances of the likelihood probability. Performance is characterized by estimating human body postures from low level visual features, showing promising results.

Tracking Human Body Pose on a Learned Smooth Space

Particle filtering is a popular method used in systems for tracking human body pose in video. One key difficulty in using particle filtering is caused by the curse of dimensionality: generally a very large number of particles is required to adequately approximate the underlying pose distribution in a high-dimensional state space. Although the number of degrees of freedom in the human body is quite large, in reality, the subset of allowable configurations in state space is generally restricted by human biomechanics, and the trajectories in this allowable subspace tend to be smooth. Therefore, a framework is proposed to learn a low-dimensional representation of the high-dimensional human poses state space. This mapping can be learned using a Gaussian Process Latent Variable Model (GPLVM) framework. One important advantage of the GPLVM framework is that both the mapping to, and mapping from the embedded space are smooth; this facilitates sampling in the low-dimensional space, and samples generated in the low-dimensional embedded space are easily mapped back into the original highdimensional space. Moreover, human body poses that are similar in the original space tend to be mapped close to each other in the embedded space; this property can be exploited when sampling in the embedded space. The proposed framework is tested in tracking 2D human body pose using a Scaled Prismatic Model. Experiments on real life video sequences demonstrate the strength of the approach. In comparison with the Multiple Hypothesis Tracking and the standard Condensation algorithm, the proposed algorithm is able to maintain tracking reliably throughout the long test sequences. It also handles singularity and self occlusion robustly.

A Self-Organizing Neural Network for Learning a Body-Centered Invariant Representation of 3-D Target Position

This paper describes a self-organizing neural network that rapidly learns a body-centered representation of 3-D target positions. This representation remains invariant under head and eye movements, and is a key component of sensory-motor systems for producing motor equivalent reaches to targets (Bullock, Grossberg, and Guenther, 1993).

Neural Representations for Sensory-Motor Control, III: Learning a Body-Centered Representation of 3-D Target Position

A neural model is described of how the brain may autonomously learn a body-centered representation of 3-D target position by combining information about retinal target position, eye position, and head position in real time. Such a body-centered spatial representation enables accurate movement commands to the limbs to be generated despite changes in the spatial relationships between the eyes, head, body, and limbs through time. The model learns a vector representation--otherwise known as a parcellated distributed representation--of target vergence with respect to the two eyes, and of the horizontal and vertical spherical angles of the target with respect to a cyclopean egocenter. Such a vergence-spherical representation has been reported in the caudal midbrain and medulla of the frog, as well as in psychophysical movement studies in humans. A head-centered vergence-spherical representation of foveated target position can be generated by two stages of opponent processing that combine corollary discharges of outflow movement signals to the two eyes. Sums and differences of opponent signals define angular and vergence coordinates, respectively. The head-centered representation interacts with a binocular visual representation of non-foveated target position to learn a visuomotor representation of both foveated and non-foveated target position that is capable of commanding yoked eye movementes. This head-centered vector representation also interacts with representations of neck movement commands to learn a body-centered estimate of target position that is capable of commanding coordinated arm movements. Learning occurs during head movements made while gaze remains fixed on a foveated target. An initial estimate is stored and a VOR-mediated gating signal prevents the stored estimate from being reset during a gaze-maintaining head movement. As the head moves, new estimates arc compared with the stored estimate to compute difference vectors which act as error signals that drive the learning process, as well as control the on-line merging of multimodal information.

Longitudinal study of changes in body mass index, anthropometric measures, dietary intake and physical activity in cohorts of school-going Irish adolescents

The prevalence of obesity worldwide has increased dramatically over the last few decades. Poor dietary habits and low levels of exercise in adolescence are often maintained into adulthood where they can impact on the incidence of obesity and chronic diseases. A 3-year longitudinal study of anthropometric, dietary and exercise parameters was carried out annually (2005 - 2007) in 3 Irish secondary schools. Anthropometric measurements were taken in each year and analysed longitudinally. Overweight and obesity were at relatively low levels in these adolescents. Height, weight, BMI, waist and hip circumferences and TST increased significantly over the 3 years. Waist-to-hip ratio (WHR) decreased significantly over time. Boys were significantly taller than girls across the 3 years. A 3-day weighed food diary was used to assess food intake by the adolescents. Analysis of dietary intake data was determined using WISP©. Mean daily energy and nutrient intakes were reported. Mean daily energy and macronutrient intakes were analysed longitudinally. The adolescents’ diet was characterised by relatively high saturated fat intakes and insufficient fruit and vegetable consumption. The dietary pattern did not change significantly over the 3 years. Boys consumed more energy than girls over the study period. A validated questionnaire was used to assess physical activity and sedentary activity levels. Boys were substantially more active and had higher energy expenditure estimates than girls throughout the study. A significant longitudinal decrease in physical activity levels among the adolescents was observed. Both genders spent more than the recommended amount of time (hrs/day) pursing sedentary activities. The dietary pattern in these Irish adolescents is relatively poor. Of additional concern is the overall longitudinal decrease in physical activity levels. Promoting consumption of a balanced diet and increased exercise levels among adolescents will help to reduce future public health care costs due to weight-related diseases.

A novel and miniaturized 433/868MHz multi-band wireless sensor platform for body sensor network applications

Body Sensor Network (BSN) technology is seeing a rapid emergence in application areas such as health, fitness and sports monitoring. Current BSN wireless sensors typically operate on a single frequency band (e.g. utilizing the IEEE 802.15.4 standard that operates at 2.45GHz) employing a single radio transceiver for wireless communications. This allows a simple wireless architecture to be realized with low cost and power consumption. However, network congestion/failure can create potential issues in terms of reliability of data transfer, quality-of-service (QOS) and data throughput for the sensor. These issues can be especially critical in healthcare monitoring applications where data availability and integrity is crucial. The addition of more than one radio has the potential to address some of the above issues. For example, multi-radio implementations can allow access to more than one network, providing increased coverage and data processing as well as improved interoperability between networks. A small number of multi-radio wireless sensor solutions exist at present but require the use of more than one radio transceiver devices to achieve multi-band operation. This paper presents the design of a novel prototype multi-radio hardware platform that uses a single radio transceiver. The proposed design allows multi-band operation in the 433/868MHz ISM bands and this, together with its low complexity and small form factor, make it suitable for a wide range of BSN applications.

Nutrition, growth and body composition in preterm infants

The goal of neonatal nutrition in the preterm infant is to achieve postnatal growth and body composition approximating that of a normal fetus of the same postmenstrual age and to obtain a functional outcome comparable to infants born at term. However, in clinical practice such a pattern is seldom achieved, with growth failure and altered body composition being extensively reported. The BabyGrow preterm nutrition study was a longitudinal, prospective, observational study designed to investigate nutrition and growth in 59 preterm infants following the implementation of evidence-based nutrition guidelines in the neonatal unit at Cork University Maternity Hospital. Nutrient delivery was precisely measured during the entire hospital stay and intakes were compared with current international recommendations. Barriers to nutrient delivery were identified across the phases of nutritional support i.e. exclusive parenteral nutrition and transition (establishment of enteral feeds) phases of nutrition and nutritional strategies to optimise nutrient delivery were proposed according to these phases. Growth was measured from birth up to 2 months corrected age and body composition was assessed in terms of fat mass and lean body mass by air displacement plethysmography (PEA POD) at 34 weeks gestation, term corrected age and 2 months corrected age. Anthropometric and body composition data in the preterm cohort were compared with a term reference group from the Cork BASELINE Birth Cohort Study (n=1070) at similar time intervals. The clinical and nutritional determinants of growth and body composition during the neonatal period were reported for the first time. These data have international relevance, informing authoritative agencies developing evidence-based practice guidelines for neonatal nutritional support. In the future, the nutritional management of preterm infants may need to be individualised to consider gestational age, birth weight as well as preterm morbidity.

Corporeal prisons: dynamics of body and mise-en-scène in three films by Paul Schrader

This thesis focuses on the complex relationship between representations of the human body and the formal processes of mise-en-scène in three consecutive films by the writer-director Paul Schrader: American Gigolo (1980), Cat People (1982) and Mishima: A Life in Four Chapters (1985). While Schrader’s work has typically been critiqued under the broad category of masculinity in crisis (and often as a subset of the films of his more famous long-time collaborator, Martin Scorsese), I focus on a fiveyear early period of his filmography when he sought to explore his key themes of bodily crisis, fragmentation and alienation through an unusually intense focus upon the expressive potential of film form, specifically via the combined elements of colour, lighting, camerawork and production design. By approaching these three films as corporeal character studies of troubled figures whose emotional and psychosexual neurosis is experienced in and through the body, I will locate Schrader’s filmmaking process and style within the thematic and aesthetic contexts of both his own early film criticism and the European and Japanese art cinemas that he claims as his primary influence. In doing so, I will establish Schrader’s position as a director whose literary and theological background differentiated him from his peers of the postclassical Hollywood generation, and who thus continually sought to develop his own visual literacy through his relationship with the camera and his collaborations with more overtly style-oriented film artists. But instead of merely focusing on mise-en-scène to gain a formalist appreciation of these films, I mobilise stylistic analysis as a new critical approach towards the problematic discourses of identity and embodiment that have haunted Schrader’s career from the beginning. In particular, I argue that paying closer attention to Schrader’s formal choices sheds new light on how these films – which he approached as exercises in style – repeatedly deal with the volatile and unavoidably body-oriented categories of race, gender and sexuality. In the process, I argue that a formalist attentiveness to mise-en-scène can also provide valuable cultural insights into Schrader’s oeuvre.

Nutrition, growth and body composition in infancy

This thesis is presented in two parts. Data for this research is from the Cork BASELINE (Babies after SCOPE, Evaluating Longitudinal Impact using Neurological and Nutritional Endpoints) Birth Cohort Study (n = 2137). In this prospective birth cohort study, pediatric follow-up with in-person appointments were repeated from the time of birth through to 2, 6 and 12 months, and at 2 years. Body composition was measured by air displacement plethysmography at birth and at 2 months using the PEA POD Infant Body Composition Tracking System. This thesis provides the first extensive report on the study’s 2 year assessment. In part one, the aims were to investigate potential early-life risk factors for childhood overweight and obesity, including rapid growth and body composition in infancy and umbilical cord concentrations of leptin and high molecular weight (HMW) adiponectin. This research is the first to describe rapid growth in early infancy in terms of changes in direct measures of body composition. These are also the first data to examine associations between umbilical cord leptin and HMW adiponectin concentrations and changes in fat and lean mass in early infancy. These data provide additional insight into characterising the growth trajectory in infancy and into the role of perinatal factors in determining infant growth and subsequent overweight/obesity risk. In part two of this thesis, the aims were to quantify vitamin D intake and status at 2 years and to investigate whether 25-hydroxyvitamin D [25(OH)D] concentrations in early pregnancy and in umbilical cord blood are associated with infant growth and body composition. There was a low prevalence of vitamin D deficiency among Irish 2 year olds (n = 742) despite a high prevalence of inadequate intakes and high latitude (51°N). Maternal 25(OH)D concentrations at 15 weeks gestation and cord 25(OH)D concentrations at delivery were not associated with infant growth or adiposity.

Walking in old age and development of metabolic syndrome: the health, aging, and body composition study.

BACKGROUND: The specific health benefits of meeting physical activity guidelines are unclear in older adults. We examined the association between meeting, not meeting, or change in status of meeting physical activity guidelines through walking and the 5-year incidence of metabolic syndrome in older adults. METHODS: A total of 1,863 Health, Aging, and Body Composition (Health ABC) Study participants aged 70-79 were followed for 5 years (1997-1998 to 2002-2003). Four walking groups were created based on self-report during years 1 and 6: Sustained low (Year 1, <150 min/week, and year 6, <150 min/week), decreased (year 1, >150 min/week, and year 6, <150 min/week), increased (year 1, <150 min/week, and year 6, >150 min/week), and sustained high (year 1, >150 min/week, and year 6, >150 min/week). Based on the Adult Treatment Panel III (ATP III) panel guidelines, the metabolic syndrome criterion was having three of five factors: Large waist circumference, elevated blood pressure, triglycerides, blood glucose, and low high-density lipoprotein (HDL) levels. RESULTS: Compared to the sustained low group, the sustained high group had a 39% reduction in odds of incident metabolic syndrome [adjusted odds ratio (OR) = 0.61; 95% confidence interval (CI), 0.40-0.93], and a significantly lower likelihood of developing the number of metabolic syndrome risk factors that the sustained low group developed over 5 years (beta = -0.16, P = 0.04). CONCLUSIONS: Meeting or exceeding the physical activity guidelines via walking significantly reduced the odds of incident metabolic syndrome and onset of new metabolic syndrome components in older adults. This protective association was found only in individuals who sustained high levels of walking for physical activity.

Body image and body satisfaction differ by race in overweight postpartum mothers.

BACKGROUND: Body image (BI) and body satisfaction may be important in understanding weight loss behaviors, particularly during the postpartum period. We assessed these constructs among African American and white overweight postpartum women. METHODS: The sample included 162 women (73 African American and 89 white) in the intervention arm 6 months into the Active Mothers Postpartum (AMP) Study, a nutritional and physical activity weight loss intervention. BIs, self-reported using the Stunkard figure rating scale, were compared assessing mean values by race. Body satisfaction was measured using body discrepancy (BD), calculated as perceived current image minus ideal image (BD<0: desire to be heavier; BD>0: desire to be lighter). BD was assessed by race for: BD(Ideal) (current image minus the ideal image) and BD(Ideal Mother) (current image minus ideal mother image). RESULTS: Compared with white women, African American women were younger and were less likely to report being married, having any college education, or residing in households with annual incomes >$30,000 (all p < 0.01). They also had a higher mean body mass index (BMI) (p = 0.04), although perceived current BI did not differ by race (p = 0.21). African Americans had higher mean ideal (p = 0.07) and ideal mother (p = 0.001) BIs compared with whites. African Americans' mean BDs (adjusting for age, BMI, education, income, marital status, and interaction terms) were significantly lower than those of whites, indicating greater body satisfaction among African Americans (BD(Ideal): 1.7 vs. 2.3, p = 0.005; BD(Ideal Mother): 1.1 vs. 1.8, p = 0.0002). CONCLUSIONS: Racial differences exist in postpartum weight, ideal images, and body satisfaction. Healthcare providers should consider tailored messaging that accounts for these racially different perceptions and factors when designing weight loss programs for overweight mothers.