Background: Pedestrian detection and tracking are an important area of study in realworld
applications, such as mobile robots, human-computer interaction, video surveillance, pedestrian
protection systems, etc. As a result, it has attracted the interest of the scientific community.
Objective: Certainly, tracking people is critical for numerous utility areas which cover unusual situations
detection, like vicinity evaluation, and sometimes change direction in human gait and partial
Researchers' primary focus is to develop a surveillance system that can work in a dynamic environment,
but there are major issues and challenges involved in designing such systems. So, it has become
a significant issue and challenge to design a tracking system that can be more suitable for such
situations. To this end, this paper presents a comparative evaluation of the tracking-by-detection
system along with the publicly available pedestrian benchmark databases.
Method: Unlike recent works where person detection and tracking are usually treated separately,
our work explores the joint use of the popular Simple Online and Real-time Tracking (SORT) method
and the relevant visual detectors. Consequently, the choice of the detector is an important factor
in the evaluation of the system's performance.
Results: Experimental results demonstrate that the performance of the tracking-by-detection system
is closely related to the optimal selection of the detector and should be required prior to a rigorous
Conclusion: The study demonstrates how sensitive the system performance as a whole is to the
challenges of the dataset. Furthermore, the efficiency of the detector and the detector-tracker combination
is also depending on the dataset.