Title

Probabilistic Cluster Signature For Modeling Motion Classes

Abstract

In this paper, a novel 3-D motion trajectory signature is introduced to serve as an effective description to the raw trajectory. More importantly, based on the trajectory signature, a probabilistic model-based cluster signature is further developed for modeling a motion class. The cluster signature is a mixture model-based motion description that is useful for motion class perception, recognition and to benefit a generalized robot task representation. The signature modeling process is supported by integrating the EM and IPRA algorithms. The conducted experiments verified the cluster signature's effectiveness. © 2009 IEEE.

Publication Date

12-11-2009

Publication Title

2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009

Number of Pages

5731-5736

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/IROS.2009.5354142

Socpus ID

76249101837 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/76249101837

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