zyinshi / Optical Flow
Implementation of Lucas-Kanade optical flow algorithm.
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matlab
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Implementation of Optical Flow Algorithm
The implementation has 4 parts:
-
Naive dense optical flow.(
opticalFlow.m) Windowsize and threshold for smallest eigen value are free parameter -
Corner-based sparse optical flow
- Corner detection is based on Gaussian deviation (
CornerDetect.m,gaussian.m,d_gaussian.m)
- Iterative Coarse to Fine Optical Flow (details can be found in
report.pdf)
- Multi-resolution pyramid (
pyramidFlow.m) - apply Lucas-Kanada optical flow iteratively to estimate potential motion velocity on each level (
iterOpticalflow.m)
- Experiments
- Motion based Background Subtraction (
bg.m) Remove the dynamic portions of an image from a static background - Motion based Image Segmentation
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