Multi-scale cortical keypoints for realtime hand tracking and gesture recognition

Human-robot interaction is an interdisciplinary research area which aims at integrating human factors, cognitive psychology and robot technology. The ultimate goal is the development of social robots. These robots are expected to work in human environments, and to understand behavior of persons through gestures and body movements. In this paper we present a biological and realtime framework for detecting and tracking hands. This framework is based on keypoints extracted from cortical V1 end-stopped cells. Detected keypoints and the cells’ responses are used to classify the junction type. By combining annotated keypoints in a hierarchical, multi-scale tree structure, moving and deformable hands can be segregated, their movements can be obtained, and they can be tracked over time. By using hand templates with keypoints at only two scales, a hand’s gestures can be recognized.

Preface

Information and Communication Technologies (ICT) play a major role in our lives. However, ICT development which is indifferent to the concerns of social inclusion may raise barriers and increase the gap between the average user and those with special needs, instead of contributing to eliminating this gap and promoting equal rights and opportunities for all. Senior citizens and others with special needs are often faced with multiple minor disabilities that prevent them from enjoying the benefits of technology and higher quality of life standards. According to the UN Convention on the Rights of Persons with Disabilities, technology design should take into account accessibility and usability features for the protection and promotion of the human rights of persons with disabilities, in all policies and programmes.

Profiles of ageing in the South of Portugal: education and cognitive functioning in elderly persons living in institutionalized and community contexts

The region of the Algarve shows huge differences between the coastline where population in the urban areas grows, and the inland rural areas, in some cases very isolated, which frequently have high ageing indexes. This general scenario, with an elderly population with very different economic and social conditions, frames the ongoing PhD research designed as a cross-sectional study of an intentional sample of elderly persons. The basic theoretical framework departs from the perspective of developmental psychology of life-span and the model of selection, optimisation and compensation for optimal ageing (Baltes & Baltes, 1990; Freund & Baltes, 2002). The present study is a first step in the analysis of empirical data collected in the PhD sample (N=156; age range 65 to 97 years; M = 80.4 years; SD = 7.2 years). Its purpose is to assess the cognitive functioning of participants, screening for cognitive impairment and examine the relations between the cognitive status of the subjects and a number of selected variables including educational level, age, physical activity and living contexts of the subjects. We accessed the cognitive status of the participants with the Portuguese version of Mini Mental State Examination (MMSE) finding a 10.3% prevalence of positive cases with cognitive impairment. The results also show significant relationships between the cognitive status accessed by the MMSE and educational level, professional qualification, age, living arrangement and activity level of the participants. The relationship verified between educational level and cognitive status of the participants was the largest correlation found in the study with the variability in educational level accounting for 44.8% of the variability in MMSE score. This results points in the same direction of several lines of research that corroborate the strong intercorrelation between education and cognitive functioning in old age.