Machine Learning Based Object Tracking

TL;DR

This paper presents a machine learning approach for object detection and tracking, integrating OpenCV for ROI selection and servo control to maintain object centering, with detailed procedures and code provided.

Contribution

It introduces a combined method of machine learning-based detection and servo-controlled tracking with comprehensive implementation details.

Findings

Successful object tracking with real-time servo adjustments

Effective use of OpenCV for ROI and tracking

Detailed procedural and code documentation

Abstract

Machine learning based object detection as well as tracking that object have been performed in this paper. The authors were able to set a range of interest (ROI) around an object using Open Computer Vision, better known as OpenCV. Next a tracking algorithm has been used to maintain tracking on an object while simultaneously operating two servo motors to keep the object centered in the frame. Detailed procedure and code are included in this paper.