Action recognition in a high-dimensional feature space [Yüksek boyutlu öznitelik uzayinda hareket tanima]
2013 21st Signal Processing and Communications Applications Conference, SIU 2013
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Please cite this item using this persistent URLhttp://hdl.handle.net/11693/28003
Analyzing and interpreting human actions is an important and challenging area of computer vision. Different solutions are used for representing human actions; we prefer to use spatio-temporal interest points for motion descriptors. Besides, the space-time interest point feature space is considerably high-dimensional and it is hard to eliminate the curse of dimensionality with traditional similarity functions. We apply a matching based approach for high dimensional feature space that matches sequences to classify actions. © 2013 IEEE.
- Conference Paper 2294
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