A Multisensor Based Approach Using Supervised Learning and Particle Filtering for People Detection and Tracking-Reference-Cited by-同舟云学术

A Multisensor Based Approach Using Supervised Learning and Particle Filtering for People Detection and Tracking

Published:2015-11-28 Issue: Volume: Page:645-657
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
Short-container-title:

Author:

Aguirre Eugenio,García-Silvente Miguel,Pascual Daniel

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-27149-1_50

Reference20 articles.

1. Aguirre, E., Garcia-Silvente, M., Plata, J.: Leg detection and tracking for amobile robot and based on a laser device, supervised learning and particle filtering. In: ROBOT2013: First Iberian Robotics Conference, volume 252 of Advances in Intelligent Systems and Computing, pages 434–440. Springer Int. Publis. (2014)

2. Aherne, F., Thacker, N., Rockett, P.: The bhattacharyya metric as an absolute similarity measure for frequency coded data. Kybernetica 32, 1–7 (1997)

3. Ansuategui, A., Ibarguren, A., Martíonez-Otzeta, J.M., Tubío, C., Lazkano, E.: Particle filtering for people following behavior using laser scans and stereo vision. International Journal on Artificial Intelligence Tools 20(02), 313–326 (2011)

4. Arulampalam, M.S., Maskell, S., Gordon, N., Clapp, T.: A tutorial on particle filters for online nonlinear/non-gaussian bayesian tracking. IEEE Transactions on Signal Processing 50(2), 174–188 (2002)

5. Bellotto, N., Hu, H.: Multisensor-based human detection and tracking for mobile service robots. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 39(1), 167–181 (2009)

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