Body surface imaging

An embodiment of the invention may provide a portable, inexpensive two-view 3D stereo vision imaging system, which acquires a 3D surface model and dimensions of an object. The system may comprise front-side and back-side stereo imagers which each have a projector and at least two digital cameras to image the object from different perspectives. An embodiment may include a method for reconstructing an image of a human body from the data of a two-view body scanner by obtaining a front scan image data point set and a back scan image data point set. A smooth body image may be gained by processing the data point sets using the following steps: (1) data resampling; (2) initial mesh generation; (3) mesh simplification; and (4) mesh subdivision and optimization.Board of Regents, University of Texas Syste

A Dense Stereovision System for 3D Body Imaging

Article presents a 3D body imaging system built upon stereovision technology which utilizes paired, high-resolution single-lens reflex (SLR) cameras to image the front and back body surfaces of a person, and robust and efficient stereo matching algorithms to reconstruct the 3D surface of the body with high-density data clouds

Preliminary results of an anthropometric data collection of portuguese children with overweight and obesity

[Excerpt] In the 21st century, according to the World Health Organization (WHO), childhood obesity has reached epidemic proportions. Worldwide, it is estimated that around 200 million children of school age have high Body Mass Index (BMI), of which 40-50 million are considered obese. [...]This work is financed by Federal Institute of Rio Grande do Sul, Brazil and FEDER funds through the Competitive Factors Operational Program (COMPETE) POCI-01-0145-FEDER-007136 and by national funds through FCT-Portuguese Foundation for Science and Technology, under the project UID/CTM/000264

Main characteristics and anthropometrics of people with down syndrome – Impact in garment design

Among the human chromosome abnormalities, Down Syndrome is the most prominent. Social perception challenges include prejudice, myth and exclusion, with social inclusion having been subject of several studies. From this perspective, the main objective of this study is to contribute to a higher social inclusion of people with Down Syndrome. This is addressed by an anthropometric characterization study of Down Syndrome individuals, performed with the technology of body scanning (3D Body Scanner). The presented study can support the development of inclusive clothing, adapted to people with special needs, promoting the anthropometric and ergonomic aspects of shape, comfort and aesthetics, which would lead to an increased quality of life, self-esteem and security, contributing to a higher inclusion in our society. The results from the data obtained through the measuring tables provided by the 3D Body Scanner System allow the identification of the main body shapes of the analyzed sample, as well as the main variables of their measurements. The impact characteristics from this specific population in the garment design process is also discussed.(UID/CTM/000264)info:eu-repo/semantics/publishedVersio

Segmentation of anthropometric data of the Brazilian’ female population

The researches concerning the measurements of the human body in Brazil are still very few and the anthropometric data related with the Brazilian women is widely diversified due to some aspects such as the vastness of the country and a huge miscegenation of races. The results obtained through the utilization of a 3D body scanner were segmented into four categories, namely: age, region of origin, race and shape. The aim of this study is to provide more accurate and reliable measurements and information concerning the different types of body shapes for the clothing sizing systems directed to the industry specialized in the mass production of clothing, and, therefore, allow clothing to fit appropriately on the wearer’s body in such a way as to make her more confident and satisfied with the clothing available in the market but also access higher levels of comfort.We would like to acknowledge 2C2T-Science Center for Textile Technology from University of Minho and Federal University of Technology – Parana (UTFPR). This work is financed by FEDER funds through the Competitive Factors Operational Program (COMPETE) POCI-01-0145-FEDER-007136 and by national funds through FCT-Portuguese Foundation for Science and Technology, under the project UID/CTM/000264.info:eu-repo/semantics/publishedVersio

IMPACT OF IMAGE RESOLUTION ON PAVEMENT DISTRESS DETECTION USING PICUCHA METHODOLOGY

An accurate and regular survey of the road surface distresses is a key factor for pavement rehabilitation design and management, allowing public managers to maximize the value of the continuously limited budgets for road improvements and maintenance. Manual pavement distress surveys are labor-intensive, expensive and unsafe for highly-trafficked highways. Over the years, automated surveys using various hardware devices have been developed and improved for pavement field data collection to solve the problems associated with manual surveys. However, the reliable distress detection software and the data analysis remain challenging. This study focused on the analysis of a newly-developed pavement distress classification algorithm, called the PICture Unsupervised Classification with Human Analysis (PICUCHA) method, particularly the impact of image resolutions on its classification accuracy. The results show that a non-linear relationship exists between the classification accuracy and the image resolution, suggesting that images with a resolution around 1.24 mm/pixel may provide the optimal classification accuracy when using the PICUCHA method. The findings of this study can help to improve more effective uses of the specialize software for pavement distress classification, to support decision makers to choose cameras according to their budgets and desired survey accuracy, and to evaluate how existing cameras will perform if used with PICUCHA

Application of Artificial Intelligence for Optimization in Pavement Management

Artificial intelligence (AI) is a group of techniques that have quite a potential to be applied to pavement engineering and management. In this study, we developed a practical, flexible and out of the box approach to apply genetic algorithms to optimizing the budget allocation and the road maintenance strategy selection for a road network. The aim is to provide an alternative to existing software and better fit the requirements of an important number of pavement managers. To meet the objectives, a new indicator, named Road Global Value Index (RGVI), was created to contemplate the pavement condition, the traffic and the economic and political importance for each and every road section. This paper describes the approach and its components by an example confirming that genetic algorithms are very effective for the intended purpose

Classifying Abdominal Fat Distribution Patterns by Using Body Measurement Data

This article aims to explore new categorization that characterizes the distribution clusters of visceral and subcutaneous adipose tissues (VAT and SAT) measured by magnetic resonance imaging (MRI), to analyze the relationship between the VAT-SAT distribution patterns and the novel body shape descriptors (BSDs), and to develop a classifier to predict the fat distribution clusters using the BSDs

3D Microscopy for High-throughput Phenotyping of Cotton Fibers

Data management plan for the grant, "3D Microscopy for High-throughput Phenotyping of Cotton Fibers.