Gilliam, ChristopherChristopherGilliamTHIERRY BLU2024-03-072024-03-072015-08-04978146736997815206149https://scholars.lib.ntu.edu.tw/handle/123456789/640505The optical flow is a velocity field that describes the motion of pixels within a sequence (or set) of images. Its estimation plays an important role in areas such as motion compensation, object tracking and image registration. In this paper, we present a novel framework to estimate the optical flow using local all-pass filters. Instead of using the optical flow equation, the framework is based on relating one image to another, on a local level, using an all-pass filter and then extracting the optical flow from the filter. Using this framework, we present a fast novel algorithm for estimating a smoothly varying optical flow, which we term the Local All-Pass (LAP) algorithm. We demonstrate that this algorithm is consistent and accurate, and that it outperforms three state-of-the-art algorithms when estimating constant and smoothly varying flows. We also show initial competitive results for real images.All-pass Filters | Approximation | Motion Estimation | Optical Flowconference paper10.1109/ICASSP.2015.71782272-s2.0-84946077634https://api.elsevier.com/content/abstract/scopus_id/84946077634