OpenCV IDEA: Lightweight Optical Flow Model

Optical flow is the problem of estimating the motion of objects in an image or video sequence. Optical flow is pivotal to many computer vision applications such as object tracking, video stabilization, and motion analysis, providing essential information about the dynamics of a scene or an object. With the upsurge in the use of deep neural networks, DNN models were developed to solve the optical flow problem, achieving state-of-the-art results by learning to estimate motion from image data. However, DNNs can become computationally expensive making it infeasible to be deployed on embedded systems. This problem is tackled by the development of lightweight DNN models. However, OpenCV model zoo hasn't had any implementation of an optical flow lightweight model yet. Thus, this project aims to find the best lightweight optical flow model in terms of model size, speed, and accuracy to introduce to the OpenCV model zoo.