Thisworkpresentsasystembasedonarecurrentdeepneural network to classify actions performed in an indoor environment. RGBD and infrared sensors positioned in the rooms are used as data source. The smart environment the user lives in can be adapted to his/her needs.

Indoor actions classification through long short term memory neural networks

Emanuele Cipolla;Ignazio Infantino;Umberto Maniscalco;Giovanni Pilato;Filippo Vella
2017

Abstract

Thisworkpresentsasystembasedonarecurrentdeepneural network to classify actions performed in an indoor environment. RGBD and infrared sensors positioned in the rooms are used as data source. The smart environment the user lives in can be adapted to his/her needs.
2017
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
Inglese
ICIAP 2017 - 19th International Conference on Image Analysis and Processing
September 13th-15th, 2017
Deep Learning
Human Actions
LSTM
Indoor Activities
5
none
Emanuele Cipolla; Ignazio Infantino; Umberto Maniscalco; Giovanni Pilato; Filippo Vella
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/337789
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