The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIV-2/W1-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-2/W1-2021, 163–166, 2021
https://doi.org/10.5194/isprs-archives-XLIV-2-W1-2021-163-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-2/W1-2021, 163–166, 2021
https://doi.org/10.5194/isprs-archives-XLIV-2-W1-2021-163-2021

  15 Apr 2021

15 Apr 2021

FREQUENCY FEATURES FOR DETECTING EVENTS IN VIDEO SEQUENCE OF VIDEO-EEG MONITORING DATA

D. Murashov1, Y. Obukhov2, I. Kershner2, and M. Sinkin3 D. Murashov et al.
  • 1Federal Research Center “Computer Science and Control” of RAS, 119333, Moscow, Russia
  • 2Kotel'nikov Institute of Radio Engineering and Electronics of RAS, 125009, Moscow, Russia
  • 3N.V. Sklifosovsky Research Institute for Emergency Medicine of Moscow Healthcare Department, 129090, Moscow, Russia

Keywords: Video-Electroencephalographic Monitoring, Optical Flow, Periodogram, Welch's Method, Clustering

Abstract. The work is devoted to the study of the frequency features of the optical flow obtained from the video record of long-term video-electroencephalographic (video-EEG) monitoring data of patients with epilepsy. It is necessary to obtain features to recognize epileptic seizures and differentiate them from non-epileptic events. We propose to analyze the periodograms of the smoothed optical flow calculated from the fragments of the patient's video recordings. We use Welch's method to obtain periodograms. The values of the power spectral density of the optical flow at the selected frequencies will be used as features. Using the clustering algorithm, four groups of events were identified in video recordings.