Year: 2012
Type: conference-paper
Abstract: 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.
Authors: Farrajota, Miguel, Saleiro, Mário, Terzic, Kasim, Rodrigues, J. M. F., du Buf, J. M. H.
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: A neuro-dynamic framework for cognitive robotics: scene representations, behavioural sequences, and learning, NEURAL CORRELATES OF MOTION AND STEREO VISION IN HUMAN POSE AND GAIT DETECTION, Blavigator: um auxilio barato e fiável para a navegação dos cegos, Projecto Estratégico - LA 9 - 2011-2012, ACTIVE VISION IN ROBOT COGNITION, G8952488736
OpenAlex ID: W2236985995