Lap-Based Video Frame Interpolation
Journal
Proceedings - International Conference on Image Processing, ICIP
Journal Volume
2019-September
ISBN
9781538662496
Date Issued
2019-09-01
Author(s)
Abstract
High-quality video frame interpolation often necessitates accurate motion estimation, which can be obtained using modern optical flow methods. In this paper, we use the recently proposed Local All-Pass (LAP) algorithm to compute the optical flow between two consecutive frames. The resulting flow field is used to perform interpolation using cubic splines. We compare the interpolation results against a well-known optical flow estimation algorithm as well as against a recent con-volutional neural network scheme for video frame interpolation. Qualitative and quantitative results show that the LAP algorithm performs fast, high-quality video frame interpolation, and perceptually outperforms the neural network and the Lucas-Kanade method on a variety of test sequences.
Subjects
Convolutional neural network | Lucas-Kanade algorithm | Optical flow | Splines | Video interpolation
Type
conference paper