Feature-Based Object Detection and Tracking: A Systematic Literature Review
Journal article, 2024

Correct object detection plays a key role in generating an accurate object tracking result. Feature-based methods have the capability of handling the critical process of extracting features of an object. This paper aims to investigate object tracking using feature-based methods in terms of (1) identifying and analyzing the existing methods; (2) reporting and scrutinizing the evaluation performance matrices and their implementation usage in measuring the effectiveness of object tracking and detection; (3) revealing and investigating the challenges that affect the accuracy performance of identified tracking methods; (4) measuring the effectiveness of identified methods in terms of revealing to what extent the challenges can impact the accuracy and precision performance based on the evaluation performance matrices reported; and (5) presenting the potential future directions for improvement. The review process of this research was conducted based on standard systematic literature review (SLR) guidelines by Kitchenam's and Charters'. Initially, 157 prospective studies were identified. Through a rigorous study selection strategy, 32 relevant studies were selected to address the listed research questions. Thirty-two methods were identified and analyzed in terms of their aims, introduced improvements, and results achieved, along with presenting a new outlook on the classification of identified methods based on the feature-based method used in detection and tracking process.

object tracking

multiple object tracking accuracy

object detection

multiple object tracking precision

object tracking challenges

Feature-based

Author

Nurul Izzatie Husna Fauzi

Malaysia University

Zalili Musa

Malaysia University

Fadhl Mohammad Omar Hujainah

Chalmers, Computer Science and Engineering (Chalmers), Interaction Design and Software Engineering

International Journal of Image and Graphics

0219-4678 (ISSN) 17936756 (eISSN)

Vol. 24 3 2450037

Subject Categories

Other Computer and Information Science

Software Engineering

Computer Vision and Robotics (Autonomous Systems)

DOI

10.1142/S0219467824500372

More information

Latest update

6/18/2024