Moving Object Detection Using Syntax Elements 


Vol. 47,  No. 5, pp. 710-720, May  2022
10.7840/kics.2022.47.5.710


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  Abstract

Detecting moving objects in video streams is one of the most prominent challenges in computer vision. Background modeling and subtraction is the most commonly used technique for motion detection. This paper proposes a technique that uses information extracted from a video stream in the compressed domain to detect objects in motion. The syntax elements that store motion information are processed and analyzed. The main objective is to extract the region of interest (ROI), which are the areas of the high-resolution video bitstream that contain objects that are moving. The objects within these regions can then be classified into respective classes. Experimental results and detailed analysis compare our proposed method to previous work. Previously used techniques can be very computationally intensive and hence challenging to perform in real-time. We also discuss at length the challenges that we come across in moving object detection.

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  Cite this article

[IEEE Style]

D. Kim, R. Koikara, S. Kim, S. Shin, J. Eom, M. Kim, J. Hong, "Moving Object Detection Using Syntax Elements," The Journal of Korean Institute of Communications and Information Sciences, vol. 47, no. 5, pp. 710-720, 2022. DOI: 10.7840/kics.2022.47.5.710.

[ACM Style]

Dong-Key Kim, Rosemary Koikara, Sun-Jung Kim, So-Myoung Shin, Jewon Eom, Min-Joong Kim, and Joo-Hee Hong. 2022. Moving Object Detection Using Syntax Elements. The Journal of Korean Institute of Communications and Information Sciences, 47, 5, (2022), 710-720. DOI: 10.7840/kics.2022.47.5.710.

[KICS Style]

Dong-Key Kim, Rosemary Koikara, Sun-Jung Kim, So-Myoung Shin, Jewon Eom, Min-Joong Kim, Joo-Hee Hong, "Moving Object Detection Using Syntax Elements," The Journal of Korean Institute of Communications and Information Sciences, vol. 47, no. 5, pp. 710-720, 5. 2022. (https://doi.org/10.7840/kics.2022.47.5.710)