Kinect and Episodic Reasoning for Human Action Recognition

Ruben Cantarero, Maria J. Santofimia, David Villa, Roberto Requena, Maria Campos, Francisco Florez-Revuelta, Jean-Christophe Nebel, Jesus Martinez del Rincon, Juan C. Lopez

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

2 Citations (Scopus)
385 Downloads (Pure)

Abstract

This paper presents a method for rational behaviour recognition that combines vision-based pose estimation with knowledge modeling and reasoning. The proposed method consists of two stages. First, RGB-D images are used in the estimation of the body postures. Then, estimated actions are evaluated to verify that they make sense. This method requires rational behaviour to be exhibited. To comply with this requirement, this work proposes a rational RGB-D dataset with two types of sequences, some for training and some for testing. Preliminary results show the addition of knowledge modeling and reasoning leads to a significant increase of recognition accuracy when compared to a system based only on computer vision.
Original languageEnglish
Title of host publicationDistributed Computing and Artificial Intelligence, 13th International Conference
Pages147-154
Number of pages8
ISBN (Electronic)978-3-319-40162-1
DOIs
Publication statusPublished - Jun 2016
Event13th International Conference on Distributed Computing and Artificial Intelligence (DCAI)) - Seville, Spain
Duration: 01 Jun 201603 Jun 2016

Publication series

NameAdvances in Intelligent Systems and Computing
PublisherSpringer International Publishing
Volume474
ISSN (Print)2194-5357

Conference

Conference13th International Conference on Distributed Computing and Artificial Intelligence (DCAI))
CountrySpain
CitySeville
Period01/06/201603/06/2016

Fingerprint Dive into the research topics of 'Kinect and Episodic Reasoning for Human Action Recognition'. Together they form a unique fingerprint.

Cite this