Tracking Humans and Objects in Video Surveillance System Using Feature-Based Method
DOI:
https://doi.org/10.15282/mekatronika.v6i2.11332Keywords:
Video Surveillance, Human Tracking, Object Tracking, Image ProcessingAbstract
In recent years, video surveillance system has emerged as one of the active research area in machine vision community. This research intends to integrate machine vision into video surveillance system in order to enhance the accurateness and robustness of video surveillance system. To realize more robust and secure video surveillance system, an automated system is needed which can detect, classify and track human and objects even when the occlusion occurs. Object tracking is one of the most crucial parts of a automated surveillance system Hence, we proposed a tracking system which includes tracking of human and vehicles in real-time surveillance system and also in solving the problem of partially occluded human by utilizing fast-computation techniques without compromising the accuracy and performance of that particular surveillance system. In this research, we track the classified human and objects using feature-based tracking for five states, which are: entering, leaving, normal, merging, and splitting. The developed system can track the human even if occlusion occurs since we used merging and splitting cases in our tracking algorithm. The overall accuracy for our proposed system in tracking human and car is fine which is at 94.74%.
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