Tabu search for human pose recognition

William Dyce 1 Nancy Rodriguez 2 Benoit Lange 3, 4 Sebastien Andary 1 Antoine Seilles 1
2 ICAR - Image & Interaction
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
4 PEQUAN - Performance et Qualité des Algorithmes Numériques
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : The use of computer vision techniques to build hands-free input devices has long been a topic of interest to researchers in the field of natural interaction. In recent years Microsoft's Kinect has brought these technologies to the layman, but the most commonly used libraries for Kinect human pose recognition are closed-source. There is not yet an accepted, effective open-source alternative upon which highly specific applications can be based. We propose a novel technique for extracting the appendage configurations of users from the Kinect camera's depth feed, based on stochastic local search techniques rather than per-pixel classification.
Document type :
Conference papers
Complete list of metadatas

Cited literature [19 references]  Display  Hide  Download
Contributor : Benoit Lange <>
Submitted on : Monday, September 8, 2014 - 10:28:01 AM
Last modification on : Friday, October 4, 2019 - 3:14:23 PM
Long-term archiving on : Tuesday, December 9, 2014 - 10:34:33 AM


Files produced by the author(s)



William Dyce, Nancy Rodriguez, Benoit Lange, Sebastien Andary, Antoine Seilles. Tabu search for human pose recognition. 3DIPM: 3D Image Processing, Measurement, Feb 2014, San Francisco, United States. ⟨10.1117/12.2040563⟩. ⟨hal-01061640⟩



Record views


Files downloads