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Image segmentation, feature description and object tracking form the foundation of many successful applications of computer vision. The objective of this task is for you to become familiar with these techniques and their implementation in OpenCV.

License: MIT License

Python 31.64% Jupyter Notebook 68.36%
python3 imageio-framework imageio numpy numpy-arrays numpy-library contours opencv cv2 shutil

realtime-object-tracking-using-opencv's Introduction

Object-Tracking-using-Opencv

Image segmentation, feature description and object tracking form the foundation of many successful applications of computer vision. The objective of this task is for you to become familiar with these techniques and their implementation in OpenCV.

Given a video with several (up to 3) objects of interest, the tasks are to detect the objects and track them through the video.

Uses feature descriptors to match objects in the model frame to those in each frame (image) of the sequence. To display the estimated object locations in each frame in the video. Display the ongoing object trajectories, based on the estimated object locations in each frame in the video.

_Sample Interaction _

https://www.youtube.com/embed/8VDF_qqcq3M

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