This dataset, presents the results of motion detection experiments conducted on five distinct datasets sourced from changedetection.net: bungalows, boats, highway, fall and pedestrians. The motion detection process was executed using two distinct algorithms: the original ViBe algorithm proposed by Barnich et al. (G-ViBe) and the CCTV-optimized ViBe algorithm known as α-ViBe.

DOI Link: 
10.21227/8v4c-a464
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[1] Jabulani Brown Mpofu, "Motion Detection for Surveillance Applications", IEEE Dataport, 2023. [Online]. Available: http://dx.doi.org/10.21227/8v4c-a464. Accessed: Feb. 10, 2025.
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doi = {10.21227/8v4c-a464},
url = {http://dx.doi.org/10.21227/8v4c-a464},
author = {Jabulani Brown Mpofu },
publisher = {IEEE Dataport},
title = {Motion Detection for Surveillance Applications},
year = {2023} }
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T1 - Motion Detection for Surveillance Applications
AU - Jabulani Brown Mpofu
PY - 2023
PB - IEEE Dataport
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Jabulani Brown Mpofu. (2023). Motion Detection for Surveillance Applications. IEEE Dataport. http://dx.doi.org/10.21227/8v4c-a464
Jabulani Brown Mpofu, 2023. Motion Detection for Surveillance Applications. Available at: http://dx.doi.org/10.21227/8v4c-a464.
Jabulani Brown Mpofu. (2023). "Motion Detection for Surveillance Applications." Web.
1. Jabulani Brown Mpofu. Motion Detection for Surveillance Applications [Internet]. IEEE Dataport; 2023. Available from : http://dx.doi.org/10.21227/8v4c-a464
Jabulani Brown Mpofu. "Motion Detection for Surveillance Applications." doi: 10.21227/8v4c-a464