Object Recognition Based on Human Actions by Using DBNs
Journal
Meeting on Image Recognition and Understanding 2008
Presentation number
IS3-3
Pages
pp.877-884
Reviewed
Not reviewed
Date
July 2008
Research fields
Pattern recognition
Key
Miki2008_MIRU (id=1034)
Abstract
On conventional research for enviornment recognition which is necessary
for robots working autonomously in an indoor enviornment, most of
previous methods are based on shape models.
In this paper, we propose a method for object recognition focused on
the relationship between human actions and objects.
Such relationship becomes obvious on human action patterns when he or
she handles an object.
To estimate object categories by using action patterns, we represent such
relationship probabilistically in Dynamic Bayesian Networks (DBN).
By learning human actions toward objects statistically, objects can be recognized.
Finally, we performed experiments and confirmed that objects can be
recognized without shape models.
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