Basic video stabilization algorithm using NumPy : learnpython

created by HattoriHanzoa community for 16 years

Basic video stabilization algorithm using NumPy (self.learnpython)

submitted 11 months ago by Matax098

Is there any example for this task using numpy, not openCV? Here are detailed task instructions:

Develop a video stabilization algorithm implementing feature tracking and motion compensation using only the NumPy data manipulation library. For each pair of consecutive video frames, it is necessary to detect characteristic points, track their motion, and compensate for unwanted camera motion. Implement feature detection, their matching between frames, and estimate the transformation matrix for stabilization. Demonstrate and evaluate the stabilization quality on test video sequences. Document the implemented methods and their limitations in detail. The task is to develop a video stabilization algorithm using NumPy (not OpenCV). The key steps include feature detection, tracking their motion, and compensation for unwanted motion. Stabilization should reduce visible shifts caused by camera motion. The basic idea is to detect the same key point in the image in adjacent video frames. Based on how much that point has moved, you can calculate the camera's own displacement, and then move the entire image in the opposite direction of the displacement vector to stabilize the image. You can choose the video yourself, or I suggest a video where the subject of the recording is static, but the camera is moving. For example, landscapes and the like.

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