Object Detection Algorithm Implementation

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Resource Overview

This program implements an object detection algorithm using the classical optical flow method, which generates a motion optical flow map as the final output.

Detailed Documentation

This document describes the working principle of the object detection algorithm program. The program employs the classical optical flow algorithm, which calculates pixel motion in images by analyzing brightness variations between pixels. In motion detection applications, optical flow algorithms are widely used because they provide valuable information about object velocity and direction. The algorithm implementation typically involves computing intensity gradients between consecutive frames and solving the optical flow equation using methods like Lucas-Kanade or Horn-Schunck. The motion optical flow map is generated by visualizing optical flow vectors, effectively displaying motion trajectories and directions within the image. This object detection algorithm implementation can therefore provide enhanced insights and information for motion detection applications, with key functions including frame differencing, gradient computation, and vector visualization.

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