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Behavior estimation for a complete framework for human motion prediction in crowded environments
dc.contributor.author | Ferrer Mínguez, Gonzalo |
dc.contributor.author | Sanfeliu Cortés, Alberto |
dc.contributor.other | Institut de Robòtica i Informàtica Industrial |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.date.accessioned | 2015-08-27T10:25:28Z |
dc.date.available | 2015-08-27T10:25:28Z |
dc.date.created | 2014 |
dc.date.issued | 2014 |
dc.identifier.citation | Ferrer, G., Sanfeliu, A. Behavior estimation for a complete framework for human motion prediction in crowded environments. A: IEEE International Conference on Robotics and Automation. "Proceedings of the 2014 IEEE International Conference on Robotics and Automation". Hong Kong: 2014, p. 5940-5945. |
dc.identifier.uri | http://hdl.handle.net/2117/76525 |
dc.description.abstract | In the present work, we propose and validate a complete probabilistic framework for human motion prediction in urban or social environments. Additionally, we formulate a powerful and useful tool: the human motion behavior estimator. Three different basic behaviors have been detected: Aware, Balanced and Unaware. Our approach is based on the Social Force Model (SFM) and the intentionality prediction BHMIP. The main contribution of the present work is to make use of the behavior estimator for formulating a reliable prediction framework of human trajectories under the influence of dynamic crowds, robots, and in general any moving obstacle. Accordingly, we have demonstrated the great performance of our long-term prediction algorithm, in real scenarios, comparing to other prediction methods. |
dc.format.extent | 6 p. |
dc.language.iso | eng |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Robòtica |
dc.subject.other | service robots |
dc.title | Behavior estimation for a complete framework for human motion prediction in crowded environments |
dc.type | Conference report |
dc.contributor.group | Universitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel·ligents |
dc.identifier.doi | 10.1109/ICRA.2014.6907734 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6907734 |
dc.rights.access | Open Access |
local.identifier.drac | 15271555 |
dc.description.version | Postprint (author’s final draft) |
local.citation.author | Ferrer, G.; Sanfeliu, A. |
local.citation.contributor | IEEE International Conference on Robotics and Automation |
local.citation.pubplace | Hong Kong |
local.citation.publicationName | Proceedings of the 2014 IEEE International Conference on Robotics and Automation |
local.citation.startingPage | 5940 |
local.citation.endingPage | 5945 |