Maximizing Efficiency in Real-Time Invariant Object Detection: A Multi-algorithm Approach

This paper addresses the dearth of research in specialized computer cursor detection within the broader field of object detection and tracking. We present a comprehensive analysis of three iterations of an algorithm designed to detect and track computer cursors across video frames. Each edition employs distinct algorithms, catering to diverse research requirements and computational constraints. Our approach seeks to strike a balance between computational efficiency and tracking accuracy through rigorous evaluation and optimization. By offering versatile tools for researchers, this work contributes to bridging the gap between theoretical frameworks in cognitive science and practical implementation of computer vision solutions.