Towards Semantic Segmentation of Human Motion Sequences

Gehrig, Dirk; Stein, Thorsten; Fischer, Andreas; Schwameder, Hermann; Schultz, Tanja

doi:10.1007/978-3-642-16111-7_50

“…For the combination of motion primitives to longer motion sequences, context-free grammars have been proposed [11]. We extended the motion recognition system in [16] to an on-line recognition system and by learning our grammar automatically. The system returns the recognized motion primitives during the performed motions in real-time.…”

Section: Related Workmentioning

confidence: 99%

Combined intention, activity, and motion recognition for a humanoid household robot

Gehrig¹,

Krauthausen²,

Rybok³

et al. 2011

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-In this paper, a multi-level approach to intention, activity, and motion recognition for a humanoid robot is proposed. Our system processes images from a monocular camera and combines this information with domain knowledge. The recognition works on-line and in real-time, it is independent of the test person, but limited to predefined view-points. Main contributions of this paper are the extensible, multi-level modeling of the robot's vision system, the efficient activity and motion recognition, and the asynchronous information fusion based on generic processing of mid-level recognition results. The complementarity of the activity and motion recognition renders the approach robust against misclassifications. Experimental results on a real-world data set of complex kitchen tasks, e.g., Prepare Cereals or Lay Table, prove the performance and robustness of the multi-level recognition approach.

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Human Hybrid Robot: a new concept for supporting manual assembly tasks

Weidner

¹

,

Kong

²

,

Wulfsberg

³

2013

Prod. Eng. Res. Devel.

View full text Add to dashboard Cite

Combined intention, activity, and motion recognition for a humanoid household robot

Gehrig

¹

,

Krauthausen²,

Rybok

³

et al. 2011

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

Self Cite

View full text Add to dashboard Cite

Abstract-In this paper, a multi-level approach to intention, activity, and motion recognition for a humanoid robot is proposed. Our system processes images from a monocular camera and combines this information with domain knowledge. The recognition works on-line and in real-time, it is independent of the test person, but limited to predefined view-points. Main contributions of this paper are the extensible, multi-level modeling of the robot's vision system, the efficient activity and motion recognition, and the asynchronous information fusion based on generic processing of mid-level recognition results. The complementarity of the activity and motion recognition renders the approach robust against misclassifications. Experimental results on a real-world data set of complex kitchen tasks, e.g., Prepare Cereals or Lay Table, prove the performance and robustness of the multi-level recognition approach.

show abstract

Towards Semantic Segmentation of Human Motion Sequences

Cited by 3 publications

References 10 publications

Combined intention, activity, and motion recognition for a humanoid household robot

Combined intention, activity, and motion recognition for a humanoid household robot

Human Hybrid Robot: a new concept for supporting manual assembly tasks

Combined intention, activity, and motion recognition for a humanoid household robot

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