Movement Direction Estimation on Video using Optical Flow Analysis on Multiple Frames

This study proposed a model for determining the movement direction of the object based on the optical flow features. To increase the speed of computational time, optical flow features derived into a Histograms of Oriented Optical Flow (HOOF). We extracted them locally on the grid with a certain size. Moreover, to determine the movement direction we also analyzed multiple frames at once. Based on the experiment results, showing that the value of accuracy, precision, and recall of the movement detection is good, amounting to 93% for accuracy, 73.07% for precision and 84.25% for recall. Furthermore, the results of testing using the best parameter shows the value of accuracy of 98.1%, 35.6% precision, 41.2% recall, and direction detection error rate (DDER) 25,28%. The results of this study are expected to provide benefits in video analysis studies such as the riots detection and abnormal movement in public places.

@article{Solichin2018,
  title     = {Movement Direction Estimation on Video using Optical Flow Analysis on Multiple Frames},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {9},
  number    = {6},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Achmad Solichin and Agus Harjoko and Agfianto Eko Putra},
  doi       = {10.14569/IJACSA.2018.090625},
  url       = {https://doi.org/10.14569/IJACSA.2018.090625}
}