Partial Similarity Human Motion Retrieval Based on Relative Geometry Features

@article{Chen2012PartialSH,
  title={Partial Similarity Human Motion Retrieval Based on Relative Geometry Features},
  author={Songle Chen and Zhengxing Sun and Yi Li and Qian Li},
  journal={2012 Fourth International Conference on Digital Home},
  year={2012},
  pages={298-303}
}
With the emergence of different kinds and styles of movements in the motion database, the methods which only support overall similarity motion retrieval can't meet the needs of practical applications. In this paper, we present an effective method based on relative geometry features to support partial similarity human motion retrieval. The key components of our approach include effective feature selection by Adaboost, initial feature weight predication for a query through regression model and… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 23 REFERENCES

Human Motion Retrieval from Hand-Drawn Sketch

  • IEEE Transactions on Visualization and Computer Graphics
  • 2012
VIEW 2 EXCERPTS

Motion Data Retrieval from Very Large Motion Databases

  • 2011 International Conference on Virtual Reality and Visualization
  • 2011
VIEW 1 EXCERPT

Indexing 3-D Human Motion Repositories for Content-Based Retrieval

  • IEEE Transactions on Information Technology in Biomedicine
  • 2009
VIEW 3 EXCERPTS

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