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URN: urn:nbn:de:swb:90-409018

Human Pose Estimation with Supervoxels

Schick, Alexander

Abstract:
This thesis investigates how segmentation as a preprocessing step can reduce both the search space as well as complexity of human pose estimation in the context of smart environments. A 3D reconstruction is computed with a voxel carving algorithm. Based on a superpixel algorithm, these voxels are segmented into supervoxels that are then applied to pictorial structures in 3D to efficiently estimate the human pose. Both static and dynamic gesture recognition applications were developed.


Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Hochschulschrift
Jahr 2014
Sprache Englisch
Identifikator KITopen ID: 1000040901
Verlag Karlsruhe
Abschlussart Dissertation
Fakultät Fakultät für Informatik (INFORMATIK)
Institut Institut für Anthropomatik und Robotik (IAR)
Prüfungsdaten 08.05.2014
Referent/Betreuer Prof. R. Stiefelhagen
Schlagworte Human Pose Estimation, Voxel Carving, Superpixels, Supervoxels, Gesture Interaction
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