Human behavior analysis from depth maps

Sergio Escalera*

*Kontaktforfatter

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

18 Citationer (Scopus)

Abstract

Pose Recovery (PR) and Human Behavior Analysis (HBA) have been a main focus of interest from the beginnings of Computer Vision and Machine Learning. PR and HBA were originally addressed by the analysis of still images and image sequences. More recent strategies consisted of Motion Capture technology (MOCAP), based on the synchronization of multiple cameras in controlled environments; and the analysis of depth maps from Time-of-Flight (ToF) technology, based on range image recording from distance sensor measurements. Recently, with the appearance of the multi-modal RGBD information provided by the low cost Kinect™ sensor (from RGB and Depth, respectively), classical methods for PR and HBA have been redefined, and new strategies have been proposed. In this paper, the recent contributions and future trends of multi-modal RGBD data analysis for PR and HBA are reviewed and discussed.

OriginalsprogEngelsk
TitelArticulated Motion and Deformable Objects - 7th International Conference, AMDO 2012, Proceedings
Antal sider11
Publikationsdato2012
Sider282-292
ISBN (Trykt)9783642315664
DOI
StatusUdgivet - 2012
Udgivet eksterntJa
Begivenhed7th International Conference on Articulated Motion and Deformable Objects, AMDO 2012 - Port d'Andratx, Mallorca, Spanien
Varighed: 11 jul. 201213 jul. 2012

Konference

Konference7th International Conference on Articulated Motion and Deformable Objects, AMDO 2012
Land/OmrådeSpanien
ByPort d'Andratx, Mallorca
Periode11/07/201213/07/2012
SponsorMinisterio de Educacion y Ciencia, Spanish Government (MEC), Conselleria d'Econ. Hisenda Innovacio (Balearic Isl. Gov.), Consell de Mallorca, Span. Assoc. Pattern Recogn. Artif. Intell. (AERFAI), Eurographics Association Spanish Section (EG)
NavnLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vol/bind7378 LNCS
ISSN0302-9743

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