Action recognition in a high-dimensional feature space [Yüksek boyutlu öznitelik uzayinda hareket tanima]
2013 21st Signal Processing and Communications Applications Conference, SIU 2013
MetadataShow full item record
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.
Showing items related by title, author, creator and subject.
Naughton, T.J.; Kreis, T.; Onural L.; Ferraro P.; Depeursinge, C.; Emery, Y.; Hennelly, B.M.; Kujawiñska, M. (2009)In digital holography, holograms are usually optically captured and then two-dimensional slices of the reconstruction volume are reconstructed by computer and displayed on a two-dimensional display. When the recording is ...
Yöntem, A.Ö.; Onural L. (2012)We propose a method and present applications of this method that converts a diffraction pattern into an elemental image set in order to display them on an integral imaging based display setup. We generate elemental images ...
Yeğin M.O.; Özbay H. (Elsevier B.V., 2016)Numerical computation of H∞ controllers for time delay systems has been a challenge since 1980s. Even though significant techniques are developed to obtain direct optimal controllers, application of these methods may require ...