Categories
DSP

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

Achmad Solichin, Agus Harjoko, and Agfianto Eko Putra

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 riots detection and abnormal movement in public places.

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Categories
DSP

Grid-based Histogram of Oriented Optical Flow for analyzing movements on video data

Detection and recognition of object movements in a video is one of the research topics that are popular today. For the purposes of the analysis of the object movements in the video, the direction of movement is the important feature. In this study, we proposed a new method for determining the direction of movement using Histogram of Oriented Optical Flow (HOOF). We extract it locally at every N-by-N grid, not the entire frame. Direction movement is determined based on the value of HOOF on every grid. We classify the direction of movement in each grid into 12 directions. We use a video from UMN datasets for testing the proposed method. The experiment results show the value of False Positive Per Grid (FPPG) is 28.32%, and False Negative Per Grid (FNPG) is 4.08%. It proved that the use of Grid-based HOOF for analyzing movements on video data is good enough and can be improved in the future studies.

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