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Int J Soc Robot (2010) 2: 1930 DOI 10.1007/s12369-009-0036-0
 

Summary: Int J Soc Robot (2010) 2: 19­30
DOI 10.1007/s12369-009-0036-0
Multi-model Hypothesis Group Tracking and Group Size
Estimation
Boris Lau · Kai O. Arras · Wolfram Burgard
Accepted: 16 December 2009 / Published online: 29 December 2009
© Springer Science & Business Media BV 2009
Abstract People tracking is essential for robots that are
supposed to interact with people. The majority of ap-
proaches track humans in the vicinity of the robot indepen-
dently. However, people typically form groups that split and
merge. These group formation processes reflect social rela-
tions and interactions that we seek to recognize in this paper.
To this end, we pose the group tracking problem as a recur-
sive multi-hypothesis model selection problem in which we
hypothesize over both, the partitioning of tracks into groups
(models) and the association of observations to tracks (as-
signments). Model hypotheses that include split, merge, and
continuation events are first generated in a data-driven man-
ner and then validated by means of the assignment probabil-

  

Source: Arras, Kai O. - Institut für Informatik, Albert-Ludwigs-Universität Freiburg

 

Collections: Computer Technologies and Information Sciences