A Multi-modal Sensing Framework for Human Activity Recognition

8 years 14 days ago

Download ceur-ws.org

Abstract. Robots for the elderly are a particular category of home assistive robots, helping people in the execution of daily life tasks to extend their independent life. Such robots should be able to determine the level of independence of the user and track its evolution over time, to adapt the assistance to the person capabilities and needs. We present an heterogeneous information management framework, allowing for the description of a wide variety of human activities in terms of multi-modal environmental and wearable sensing data and providing accurate knowledge about the user activity to any assistive robot.

Barbara Bruno, Jasmin Grosinger, Fulvio Mastrogiov

Real-time Traffic

AIIA 2015 | Artificial Intelligence |

claim paper

» Motif Discovery and Feature Selection for CRFBased Activity Recognition

» Interactive MultiModal Robot Programming

» Intelligent multimodal and hyperspectral sensing for realtime moving target tracking

» SensorBased Human Activity Recognition in a Multiuser Scenario

» A framework of energy efficient mobile sensing for automatic user state recognition

» Active Capacitive Sensing Exploring a New Wearable Sensing Modality for Activity Recogniti...

» Modeling Sense Disambiguation of Human Pose Recognizing Action at a Distance by Key Poses

» Some sensor network elements for ubiquitous computing

» A LongTerm Evaluation of Sensing Modalities for Activity Recognition

Post Info
More Details (n/a)

Added	14 Apr 2016
Updated	14 Apr 2016
Type	Journal
Year	2015
Where	AIIA
Authors	Barbara Bruno, Jasmin Grosinger, Fulvio Mastrogiovanni, Federico Pecora, Alessandro Saffiotti, Subhash Sathyakeerthy, Antonio Sgorbissa

Comments (0)

Sciweavers

A Multi-modal Sensing Framework for Human Activity Recognition

AIIA 2015 | Artificial Intelligence |

Explore & Download

Productivity Tools

Document Tools

Image Tools

Sciweavers