Estimating human motion from multiple Kinect sensors

Stylianos Asteriadis, Anargyros Chatzitofis, Dimitrios Zarpalas, Dimitrios S. Alexiadis, Petros Daras

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

Abstract

Human motion estimation is a topic receiving high attention during the last decades. There is a vast range of applications that employ human motion tracking, while the industry is continuously offering novel motion tracking systems, which are opening new paths compared to traditionally used pas-sive cameras. Motion tracking algorithms, in their general form, estimate the skeletal structure of the human body and consider it as a set of joints and limbs. However, human motion tracking systems usually work on a single sensor ba-sis, hypothesizing on occluded parts. We hereby present a methodology for fusing information from multiple sensors (Microsoft's Kinect sensors were utilized in this work) based on a series of factors that can alleviate from the problem of occlusion or noisy estimates of 3D joints' positions.
Original languageEnglish
Title of host publicationProceedings of the 6th International Conference on Computer Vision / Computer Graphics Collaboration Techniques and Applications - MIRAGE '13
Pages1
Number of pages1
DOIs
Publication statusPublished - 2013
Externally publishedYes

Publication series

SeriesProceedings of the 6th International Conference on Computer Vision / Computer Graphics Collaboration Techniques and Applications - MIRAGE '13

Keywords

  • kinect-based motion detection
  • multiple kinects
  • skeleton

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