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auvsi-cv-motionestimation icon auvsi-cv-motionestimation

Learn how we perceive motion and how to estimate motion using a technique called Optical Flow. You can use three algorithms to implement optical flow using the Computer Vision Toolbox. These three algorithms are Horn-Schunck method, Farneback method, and Lucas-Kanade method. An example of a robot boat moving through a field of buoys will be used.

avatar icon avatar

Realtime facial motion capture, head pose estimation and rendering of the avatar

deep_motion_mag icon deep_motion_mag

Tensorflow implementation of Learning-based Video Motion Magnification

heartbeat icon heartbeat

Desktop implementation of Remote Photoplethysmography – Measuring heart rate using facial video.

learningrigidity icon learningrigidity

Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field Estimation (ECCV 2018)

orq icon orq

An Open-Source RaptorQ Implementation in C++

pbmoma icon pbmoma

Phase based video motion magnification

phasebasedinterpolation icon phasebasedinterpolation

This is a personal reimplementation of Phase-Based Frame Interpolation for Video [Meyer et al. 2015]

pysot icon pysot

Surrogate Optimization Toolbox for Python

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