Using facial feature extraction to enhance the creation of 3D human models

The creation of personalised 3D characters has evolved to provide a high degree of realism in both appearance and animation. Further to the creation of generic characters the capabilities exist to create a personalised character from images of an individual. This provides the possibility of immersing an individual into a virtual world. Feature detection, particularly on the face, can be used to greatly enhance the realism of the model. To address this innovative contour based templates are used to extract an individual from four orthogonal views providing localisation of the face. Then adaptive facial feature extraction from multiple views is used to enhance the realism of the model

Active meshes for motion tracking

This thesis presents an integrated approach to modelling, extraction and tracking of deformable contour meshes through image sequences, with the aim of extracting motion information about the viewed scene. The thesis begins by reviewing the area of motion estimation in computer vision, leading to a review on the formulation and initialisation of active contour models. From this review the thesis develops and provides as its major contribution an active mesh structure that may be used for motion estimation. This active mesh structure approach is combined with feature matching to provide a stable, deformable motion tracking system for real-world scenes. This system is tested on various real-world scenes and varying conditions to provide extensive and rigorous experimental proof of the validity of the formulation. Further extensions to the system are implemented, including the use of multiple and region based active meshes. Future directions of research are also suggested

A dynamic-shape-prior guided snake model with application in visually tracking dense cell populations

This paper proposes a dynamic-shape-prior guided snake (DSP G-snake) model that is designed to improve the overall stability of the point-based snake model. The dynamic shape prior is first proposed for snakes, that efficiently unifies different types of high-level priors into a new force term. To be specific, a global-topology regularity is first introduced that settles the inherent self-intersection problem with snakes. The problem that a snake’s snaxels tend to unevenly distribute along the contour is also handled, leading to good parameterization. Unlike existing methods that employ learning templates or commonly enforce hard priors, the dynamic-template scheme strongly respects the deformation flexibility of the model, while retaining a decent global topology for the snake. It is verified by experiments that the proposed algorithm can effectively prevent snakes from selfcrossing, or automatically untie an already self-intersected contour. In addition, the proposed model is combined with existing forces and applied to the very challenging task of tracking dense biological cell populations. The DSP G-snake model has enabled an improvement of up to 30% in tracking accuracy with respect to regular model-based approaches. Through experiments on real cellular datasets, with highly dense populations and relatively large displacements, it is confirmed that the proposed approach has enabled superior performance, in comparison to modern active-contour competitors as well as the state-of-the-art cell tracking frameworks

Enhancing CLIP with GPT-4: Harnessing Visual Descriptions as Prompts

Contrastive pretrained large Vision-Language Models (VLMs) like CLIP have revolutionized visual representation learning by providing good performance on downstream datasets. VLMs are 0-shot adapted to a downstream dataset by designing prompts that are relevant to the dataset. Such prompt engineering makes use of domain expertise and a validation dataset. Meanwhile, recent developments in generative pretrained models like GPT-4 mean they can be used as advanced internet search tools. They can also be manipulated to provide visual information in any structure. In this work, we show that GPT-4 can be used to generate text that is visually descriptive and how this can be used to adapt CLIP to downstream tasks. We show considerable improvements in 0-shot transfer accuracy on specialized fine-grained datasets like EuroSAT (~7%), DTD (~7%), SUN397 (~4.6%), and CUB (~3.3%) when compared to CLIP's default prompt. We also design a simple few-shot adapter that learns to choose the best possible sentences to construct generalizable classifiers that outperform the recently proposed CoCoOP by ~2% on average and by over 4% on 4 specialized fine-grained datasets. We will release the code, prompts, and auxiliary text dataset upon acceptance.Comment: 10 pages, Pre-prin

Enhancing clip with gpt-4: harnessing visual descriptions as prompts

Contrastive pretrained large Vision-Language Models (VLMs) like CLIP have revolutionized visual representation learning by providing good performance on downstream datasets. VLMs are 0-shot adapted to a downstream dataset by designing prompts that are relevant to the dataset. Such prompt engineering makes use of domain expertise and a validation dataset. Meanwhile, recent developments in generative pretrained models like GPT-4 mean they can be used as advanced internet search tools. They can also be manipulated to provide visual information in any structure. In this work, we show that GPT-4 can be used to generate text that is visually descriptive and how this can be used to adapt CLIP to downstream tasks. We show considerable improvements in 0-shot transfer accuracy on specialized fine-grained datasets like EuroSAT (~7%), DTD (~7%), SUN397 (~4.6%), and CUB (~3.3%) when compared to CLIP's default prompt. We also design a simple few-shot adapter that learns to choose the best possible sentences to construct generalizable classifiers that outperform the recently proposed CoCoOP by ~2% on average and by over 4% on 4 specialized fine-grained datasets. The code, prompts, and auxiliary text dataset is available at this https URL

Co-prevalent infections in adults with HIV-associated cryptococcal meningitis are associated with an increased risk of death: a nested analysis of the Advancing Cryptococcal meningitis Treatment for Africa (ACTA) cohort

Background: HIV-associated cryptococcal meningitis accounts for 15% of AIDS related deaths globally. In sub-Saharan Africa, acute mortality ranges from 24% to 100%. In addition to the mortality directly associated with cryptococcosis, patients with HIV-associated cryptococcal meningitis are at risk of a range of opportunistic infections (OIs) and hospital acquired nosocomial infections (HAIs). The attributable mortality associated with co-prevalent infections in cryptococcal meningitis has not been evaluated. Methods: As part of the Advancing Cryptococcal meningitis Treatment for Africa (ACTA) trial, consecutive HIV-positive adults with cryptococcal meningitis were randomised to one of five anti-fungal regimens and followed up until 10-weeks. We conducted a retrospective case note review of ACTA participants recruited from Queen Elizabeth Central Hospital in Blantyre, Malawi to describe the range and prevalence of OIs and HAIs diagnosed, and the attributable mortality associated with these infections. Results: We describe the prevalence of OIs and HAIs in 226 participants. Baseline median CD4 count was 29 cell/mm3, 57% (129/226) were on anti-retroviral therapy. 56% (127/226) had at least one co-prevalent infection during the 10-week study period. Data were collected for 187 co-prevalent infection episodes. Suspected blood stream infection was the commonest co-prevalent infection diagnosed (34/187, 18%), followed by community-acquired pneumonia (32/187, 17%), hospital-acquired pneumonia (13/187, 7%), pulmonary tuberculosis (12/187, 6%) and confirmed blood stream infections (10/187, 5%). All-cause mortality at 10-weeks was 35% (80/226), diagnosis of an OI or HAI increased the risk of death at 10 weeks by nearly 50% (HR 1.48, 95% CI 1.01-2.17, p=0.04). Conclusion: We demonstrate the high prevalence and broad range of OIs and HAIs occurring in patients with HIV-associated cryptococcal meningitis. These co-prevalent infections are associated with a significantly increased risk of death. Whether a protocolised approach to improve surveillance and proactive treatment of co-prevalent infections would improve cryptococcal meningitis outcomes warrants further investigation

Variability of Intensive Care Admission Decisions for the Very Elderly

Although increasing numbers of very elderly patients are requiring intensive care, few large sample studies have investigated ICU admission of very elderly patients. Data on pre triage by physicians from other specialities is limited. This observational cohort study aims at examining inter-hospital variability of ICU admission rates and its association with patients' outcomes. All patients over 80 years possibly qualifying for ICU admission who presented to the emergency departments (ED) of 15 hospitals in the Paris (France) area during a one-year period were prospectively included in the study. Main outcome measures were ICU eligibility, as assessed by the ED and ICU physicians; in-hospital mortality; and vital and functional status 6 months after the ED visit. 2646 patients (median age 86; interquartile range 83–91) were included in the study. 94% of participants completed follow-up (n = 2495). 12.4% (n = 329) of participants were deemed eligible for ICU admission by ED physicians and intensivists. The overall in-hospital and 6-month mortality rates were respectively 27.2% (n = 717) and 50.7% (n = 1264). At six months, 57.5% (n = 1433) of patients had died or had a functional deterioration. Rates of patients deemed eligible for ICU admission ranged from 5.6% to 38.8% across the participating centers, and this variability persisted after adjustment for patients' characteristics. Despite this variability, we found no association between level of ICU eligibility and either in-hospital death or six-month death or functional deterioration. In France, the likelihood that a very elderly person will be admitted to an ICU varies widely from one hospital to another. Influence of intensive care admission on patients' outcome remains unclear

Case Reports1. A Late Presentation of Loeys-Dietz Syndrome: Beware of TGFβ Receptor Mutations in Benign Joint Hypermobility

Background: Thoracic aortic aneurysms (TAA) and dissections are not uncommon causes of sudden death in young adults. Loeys-Dietz syndrome (LDS) is a rare, recently described, autosomal dominant, connective tissue disease characterized by aggressive arterial aneurysms, resulting from mutations in the transforming growth factor beta (TGFβ) receptor genes TGFBR1 and TGFBR2. Mean age at death is 26.1 years, most often due to aortic dissection. We report an unusually late presentation of LDS, diagnosed following elective surgery in a female with a long history of joint hypermobility. Methods: A 51-year-old Caucasian lady complained of chest pain and headache following a dural leak from spinal anaesthesia for an elective ankle arthroscopy. CT scan and echocardiography demonstrated a dilated aortic root and significant aortic regurgitation. MRA demonstrated aortic tortuosity, an infrarenal aortic aneurysm and aneurysms in the left renal and right internal mammary arteries. She underwent aortic root repair and aortic valve replacement. She had a background of long-standing joint pains secondary to hypermobility, easy bruising, unusual fracture susceptibility and mild bronchiectasis. She had one healthy child age 32, after which she suffered a uterine prolapse. Examination revealed mild Marfanoid features. Uvula, skin and ophthalmological examination was normal. Results: Fibrillin-1 testing for Marfan syndrome (MFS) was negative. Detection of a c.1270G > C (p.Gly424Arg) TGFBR2 mutation confirmed the diagnosis of LDS. Losartan was started for vascular protection. Conclusions: LDS is a severe inherited vasculopathy that usually presents in childhood. It is characterized by aortic root dilatation and ascending aneurysms. There is a higher risk of aortic dissection compared with MFS. Clinical features overlap with MFS and Ehlers Danlos syndrome Type IV, but differentiating dysmorphogenic features include ocular hypertelorism, bifid uvula and cleft palate. Echocardiography and MRA or CT scanning from head to pelvis is recommended to establish the extent of vascular involvement. Management involves early surgical intervention, including early valve-sparing aortic root replacement, genetic counselling and close monitoring in pregnancy. Despite being caused by loss of function mutations in either TGFβ receptor, paradoxical activation of TGFβ signalling is seen, suggesting that TGFβ antagonism may confer disease modifying effects similar to those observed in MFS. TGFβ antagonism can be achieved with angiotensin antagonists, such as Losartan, which is able to delay aortic aneurysm development in preclinical models and in patients with MFS. Our case emphasizes the importance of timely recognition of vasculopathy syndromes in patients with hypermobility and the need for early surgical intervention. It also highlights their heterogeneity and the potential for late presentation. Disclosures: The authors have declared no conflicts of interes

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders