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dc.contributor.authorAgethen, Philippen_US
dc.contributor.authorNeher, Thomasen_US
dc.contributor.authorGaisbauer, Felixen_US
dc.contributor.authorManns, Martinen_US
dc.contributor.authorRukzio, Enricoen_US
dc.contributor.editorJain, Eakta and Kosinka, Jiríen_US
dc.date.accessioned2018-04-14T18:29:51Z
dc.date.available2018-04-14T18:29:51Z
dc.date.issued2018
dc.identifier.issn1017-4656
dc.identifier.urihttp://dx.doi.org/10.2312/egp.20181009
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/egp20181009
dc.description.abstractThis paper presents an approach that combines a hybrid A* path planner with a statistical motion graph to effectively generate a rich repertoire of walking trajectories. The motion graph is generated from a comprehensive database (20 000 steps) of captured human motion and covers a wide range of gait variants. The hybrid A* path planner can be regarded as an orchestrationinstance, stitching together succeeding left and right steps, which were drawn from the statistical motion model. Moreover, the hybrid A* planner ensures a collision-free path between a start and an end point. A preliminary evaluation underlines the evident benefits of the proposed algorithm.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.subjectAnimation
dc.subjectModel development and analysis
dc.subjectMotion capture
dc.titleA Probabilistic Motion Planning Algorithm for Realistic Walk Path Simulationen_US
dc.description.seriesinformationEG 2018 - Posters
dc.description.sectionheadersPosters
dc.identifier.doi10.2312/egp.20181009
dc.identifier.pages3-4


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