Fast Face Detector Training Using Tailored Views

Face detection is an important task in computer vision and often serves as the first step for a variety of applications. State-of-the-art approaches use efficient learning algorithms and train on large amounts of manually labeled imagery. Acquiring appropriate training images, however, is very time-consuming and does not guarantee that the collected training data is representative in terms of data variability. Moreover, available data sets are often acquired under con-trolled settings, restricting, for example, scene illumination or 3D head pose to a narrow range. This paper takes a look into the automated generation of adaptive training samples from a 3D morphable face model. Using statistical insights, the tailored training data guarantees full data variability and is enriched by arbitrary facial attributes such as age or body weight. Moreover, it can automatically adapt to environmental constraints, such as illumination or viewing angle of recorded video footage from surveillance cameras. We use the tailored imagery to train a new many-core imple-mentation of Viola Jones ’ AdaBoost object detection frame-work. The new implementation is not only faster but also enables the use of multiple feature channels such as color features at training time. In our experiments we trained seven view-dependent face detectors and evaluate these on the Face Detection Data Set and Benchmark (FDDB). Our experiments show that the use of tailored training imagery outperforms state-of-the-art approaches on this challenging dataset. 1

Vehicle Detection Using Alex Net and Faster R-CNN Deep Learning Models: A Comparative Study

This paper has been presented at : 5th International Visual Informatics Conference (IVIC 2017)This paper presents a comparative study of two deep learning models used here for vehicle detection. Alex Net and Faster R-CNN are compared with the analysis of an urban video sequence. Several tests were carried to evaluate the quality of detections, failure rates and times employed to complete the detection task. The results allow to obtain important conclusions regarding the architectures and strategies used for implementing such network for the task of video detection, encouraging future research in this topic.S.A. Velastin is grateful to funding received from the Universidad Carlos III de Madrid, the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 600371, el Ministerio de Economía y Competitividad (COFUND2013-51509) and Banco Santander. The authors wish to thank Dr. Fei Yin for the code for metrics employed for evaluations. Finally, we gratefully acknowledge the support of NVIDIA Corporation with the donation of the GPUs used for this research. The data and code used for this work is available upon request from the authors

Bacterial Endophytes Enhance Competition by Invasive Plants

Premise of the study: Invasive plants can alter soil microbial communities and profoundly alter ecosystem processes. In the invasive grass Sorghum halepense, these disruptions are consequences of rhizome-associated bacterial endophytes. We describe the effects of N2-fixing bacterial strains from S. halepense (Rout and Chrzanowski, 2009) on plant growth and show that bacteria interact with the plant to alter soil nutrient cycles, enabling persistence of the invasive. Methods: We assessed fluxes in soil nutrients for ~4 yr across a site invaded by S. halepense. We assayed the N2-fixing bacteria in vitro for phosphate solubilization, iron chelation, and production of the plant-growth hormone indole-3-acetic acid (IAA). We assessed the plant’s ability to recruit bacterial partners from substrates and vertically transmit endophytes to seeds and used an antibiotic approach to inhibit bacterial activity in planta and assess microbial contributions to plant growth. Key results: We found persistent alterations to eight biogeochemical cycles (including nitrogen, phosphorus, and iron) in soils invaded by S. halepense. In this context, three bacterial isolates solubilized phosphate, and all produced iron siderophores and IAA in vitro. In growth chamber experiments, bacteria were transmitted vertically, and molecular analysis of bacterial community fingerprints from rhizomes indicated that endophytes are also horizontally recruited. Inhibiting bacterial activity with antibiotics resulted in significant declines in plant growth rate and biomass, with pronounced rhizome reductions. Conclusions: This work suggests a major role of endophytes on growth and resource allocation of an invasive plant. Indeed, bacterial isolate physiology is correlated with invader effects on biogeochemical cycles of nitrogen, phosphate, and iron

Cytotoxicity of ZnO Nanoparticles Can Be Tailored by Modifying Their Surface Structure: A Green Chemistry Approach for Safer Nanomaterials

ZnO nanoparticles (NP) are extensively used in numerous nanotechnology applications; however, they also happen to be one of the most toxic nanomaterials. This raises significant environmental and health concerns and calls for the need to develop new synthetic approaches to produce safer ZnO NP, while preserving their attractive optical, electronic, and structural properties. In this work, we demonstrate that the cytotoxicity of ZnO NP can be tailored by modifying their surface-bound chemical groups, while maintaining the core ZnO structure and related properties. Two equally sized (9.26 ± 0.11 nm) ZnO NP samples were synthesized from the same zinc acetate precursor using a forced hydrolysis process, and their surface chemical structures were modified by using different reaction solvents. X-ray diffraction and optical studies showed that the lattice parameters, optical properties, and band gap (3.44 eV) of the two ZnO NP samples were similar. However, FTIR spectroscopy showed significant differences in the surface structures and surface-bound chemical groups. This led to major differences in the zeta potential, hydrodynamic size, photocatalytic rate constant, and more importantly, their cytotoxic effects on Hut-78 cancer cells. The ZnO NP sample with the higher zeta potential and catalytic activity displayed a 1.5-fold stronger cytotoxic effect on cancer cells. These results suggest that by modifying the synthesis parameters/conditions and the surface chemical structures of the nanocrystals, their surface charge density, catalytic activity, and cytotoxicity can be tailored. This provides a green chemistry approach to produce safer ZnO NP

Post-TB health and wellbeing

TB affects around 10.6 million people each year and there are now around 155 million TB survivors. TB and its treatments can lead to permanently impaired health and wellbeing. In 2019, representatives of TB affected communities attending the ‘1st International Post-Tuberculosis Symposium´ called for the development of clinical guidance on these issues. This clinical statement on post-TB health and wellbeing responds to this call and builds on the work of the symposium, which brought together TB survivors, healthcare professionals and researchers. Our document offers expert opinion and, where possible, evidence-based guidance to aid clinicians in the diagnosis and management of post-TB conditions and research in this field. It covers all aspects of post-TB, including economic, social and psychological wellbeing, post TB lung disease (PTLD), cardiovascular and pericardial disease, neurological disability, effects in adolescents and children, and future research needs

Confronting historical legacies of biological anthropology in South Africa-Restitution, redress and community-centered science: The Sutherland Nine

We describe a process of restitution of nine unethically acquired human skeletons to their families, together with attempts at redress. Between 1925-1927 C.E., the skeletonised remains of nine San or Khoekhoe people, eight of them known-in-life, were removed from their graves on the farm Kruisrivier, near Sutherland in the Northern Cape Province of South Africa. They were donated to the Anatomy Department at the University of Cape Town. This was done without the knowledge or permission of their families. The donor was a medical student who removed the remains from the labourers' cemetery on his family farm. Nearly 100 years later, the remains are being returned to their community, accompanied by a range of community-driven interdisciplinary historical, archaeological and analytical (osteobiographic, craniofacial, ancient DNA, stable isotope) studies to document, as far as possible, their lives and deaths. The restitution process began by contacting families living in the same area with the same surnames as the deceased. The restitution and redress process prioritises the descendant families' memories, wishes and desire to understand the situation, and learn more about their ancestors. The descendant families have described the process as helping them to reconnect with their ancestors. A richer appreciation of their ancestors' lives, gained in part from scientific analyses, culminating with reburial, is hoped to aid the descendant families and wider community in [re-]connecting with their heritage and culture, and contribute to restorative justice, reconciliation and healing while confronting a traumatic historical moment. While these nine individuals were exhumed as specimens, they will be reburied as people

Sign Language Recognition

This chapter covers the key aspects of sign-language recognition (SLR), starting with a brief introduction to the motivations and requirements, followed by a précis of sign linguistics and their impact on the field. The types of data available and the relative merits are explored allowing examination of the features which can be extracted. Classifying the manual aspects of sign (similar to gestures) is then discussed from a tracking and non-tracking viewpoint before summarising some of the approaches to the non-manual aspects of sign languages. Methods for combining the sign classification results into full SLR are given showing the progression towards speech recognition techniques and the further adaptations required for the sign specific case. Finally the current frontiers are discussed and the recent research presented. This covers the task of continuous sign recognition, the work towards true signer independence, how to effectively combine the different modalities of sign, making use of the current linguistic research and adapting to larger more noisy data set

Specular reflection reduction with multi-flash imaging

We present a novel method to reduce the effect of specularities in digital images. Our approach relies on a simple modification of the capture setup: a multi-flash camera is used to take multiple pictures of the scene, each one with a differently positioned light source. We then formulate the problem of specular highlights reduction as solving a Poisson equation on a gradient field obtained from the input images. Experimental results are demonstrated on real and synthetic images. The entire setup can be conceivably packaged into a self-contained device, no larger than existing digital cameras