Covariate conscious approach for Gait recognition based upon Zernike moment invariants

Gait recognition i.e. identification of an individual from his/her walking pattern is an emerging field. While existing gait recognition techniques perform satisfactorily in normal walking conditions, there performance tend to suffer drastically with variations in clothing and carrying conditions. In this work, we propose a novel covariate cognizant framework to deal with the presence of such covariates. We describe gait motion by forming a single 2D spatio-temporal template from video sequence, called Average Energy Silhouette image (AESI). Zernike moment invariants (ZMIs) are then computed to screen the parts of AESI infected with covariates. Following this, features are extracted from Spatial Distribution of Oriented Gradients (SDOGs) and novel Mean of Directional Pixels (MDPs) methods. The obtained features are fused together to form the final well-endowed feature set. Experimental evaluation of the proposed framework on three publicly available datasets i.e. CASIA dataset B, OU-ISIR Treadmill dataset B and USF Human-ID challenge dataset with recently published gait recognition approaches, prove its superior performance.Comment: 11 page

Enhancing the employability of fashion students through the use of 3D CAD

The textile and apparel industry has one of the longest and most intricate supply chains within manufacturing. Advancement in technology has facilitated its globalisation, enabling companies to span geographical borders. This has led to new methods of communication using electronic data formats. Throughout the latter part of the 20th Century, 2D CAD technology established itself as an invaluable tool within design and product development. More recently 3D virtual simulation software has made small but significant steps within this market. The technological revolution has opened significant opportunities for those forward thinking companies that are beginning to utilise 3D software. This advanced technology requires designers with unique skill sets. This paper investigates the skills required by fashion graduates from an industry perspective. To reflect current industrial working practices, it is essential for educational establishments to incorporate technologies that will enhance the employability of graduates. This study developed an adapted action research model based on the work of Kurt Lewin, which reviewed the learning and teaching of 3D CAD within higher education. It encompassed the selection of 3D CAD software development, analysis of industry requirements, and the implementation of 3D CAD into the learning and teaching of a selection of fashion students over a three year period. Six interviews were undertaken with industrial design and product development specialists to determine: current working practices, opinions of virtual 3D software and graduate skill requirements. It was found that the companies had similar working practices independent of the software utilised within their product development process. The companies which employed 3D CAD software considered further developments were required before the technology could be fully integrated. Further to this it was concluded that it was beneficial for graduates to be furnished with knowledge of emerging technologies which reflect industry and enhance their employability skills

JENTIL: responsive clothing that promotes an ‘holistic approach to fashion as a new vehicle to treat psychological conditions’

This paper explores an ongoing interdisciplinary research project at the cutting edge of sensory, aroma and medical work, which seeks to change the experience of fragrance to a more intimate communication of identity, by employing emerging technologies with the ancient art of perfumery. The project illustrates .holistic' clothing called the JENTIL® Collection, following on from the Author’s SmartSecondSkin' PhD research, which describes a new movement in functional, emotional clothing that incorporates scent. The project investigates the emergent interface between the arts and biomedical sciences, around new emerging technologies and science platforms, and their applications in the domain of health and well-being. The JENTIL® Collection focuses on the development of .gentle., responsive clothing that changes with emotion, since the garments are designed for psychological end benefit to reduce stress. This is achieved by studying the mind and advancing knowledge and understanding of how known well-being fragrances embedded in holistic Fashion, could impact on mental health. This paper aims to combine applied theories about human well-being, with multisensory design, in order to create experimental strategies to improve self and social confidence for individuals suffering from depressive illnesses. The range of methodologies employed extends beyond the realm of fashion and textile techniques, to areas such as neuroscience, psychiatry, human sensory systems and affective states, and the increase in popularity of complementary therapies. In this paper the known affective potential of the sense of smell is discussed, by introducing Aroma-Chology as a tool that is worn as an emotional support system to create a personal scent bubble. around the body, with the capacity to regulate mood, physiological and psychological state and improve self-confidence in social situations. The clothing formulates a healing platform around the wearer, by creating novel olfactory experiences in textiles that are not as passive as current microencapsulated capsule systems generally are

Assistive robotics: research challenges and ethics education initiatives

Assistive robotics is a fast growing field aimed at helping healthcarers in hospitals, rehabilitation centers and nursery homes, as well as empowering people with reduced mobility at home, so that they can autonomously fulfill their daily living activities. The need to function in dynamic human-centered environments poses new research challenges: robotic assistants need to have friendly interfaces, be highly adaptable and customizable, very compliant and intrinsically safe to people, as well as able to handle deformable materials. Besides technical challenges, assistive robotics raises also ethical defies, which have led to the emergence of a new discipline: Roboethics. Several institutions are developing regulations and standards, and many ethics education initiatives include contents on human-robot interaction and human dignity in assistive situations. In this paper, the state of the art in assistive robotics is briefly reviewed, and educational materials from a university course on Ethics in Social Robotics and AI focusing on the assistive context are presented.Peer ReviewedPostprint (author's final draft

Knitwear customisation as repeated redesign

Producing large numbers of garment variants will only be economically viable if it requires very little human effort. But garment customisation cannot always be fully automated. Applying grading rules maintain the same details but sometimes achieves a different overall effect; but the customer expects the same overall effect and is less concerned about details. Choosing between alternative customisations requires a human designer's trained perceptual judgement. Therefore a viable mass customisation support system must support the repeated redesign of a garment by combining automatic design with fast human editing. Evaluating and modifying the suggestions of others is a natural and efficient activity for designers. This paper describes two prototype automatic design systems exploring techniques that could be used for mass customisation of knitted garments – in which the shape and patterns are indivisibly linked. An early pattern placing system that automatically altered both shape and pattern parameters in a variety of alternative ways. A shape design system that generates technically correct and consistent garment shapes from a set of measurements and a verbal description; it works independently of sizes, recalculating the shape for each new set of measurements. Starting from the system's suggestions, designers can very quickly tweak the new design to fulfil their aesthetic intentions

Gait recognition based on shape and motion analysis of silhouette contours

This paper presents a three-phase gait recognition method that analyses the spatio-temporal shape and dynamic motion (STS-DM) characteristics of a human subject’s silhouettes to identify the subject in the presence of most of the challenging factors that affect existing gait recognition systems. In phase 1, phase-weighted magnitude spectra of the Fourier descriptor of the silhouette contours at ten phases of a gait period are used to analyse the spatio-temporal changes of the subject’s shape. A component-based Fourier descriptor based on anatomical studies of human body is used to achieve robustness against shape variations caused by all common types of small carrying conditions with folded hands, at the subject’s back and in upright position. In phase 2, a full-body shape and motion analysis is performed by fitting ellipses to contour segments of ten phases of a gait period and using a histogram matching with Bhattacharyya distance of parameters of the ellipses as dissimilarity scores. In phase 3, dynamic time warping is used to analyse the angular rotation pattern of the subject’s leading knee with a consideration of arm-swing over a gait period to achieve identification that is invariant to walking speed, limited clothing variations, hair style changes and shadows under feet. The match scores generated in the three phases are fused using weight-based score-level fusion for robust identification in the presence of missing and distorted frames, and occlusion in the scene. Experimental analyses on various publicly available data sets show that STS-DM outperforms several state-of-the-art gait recognition methods