Feature-based motion compensated interpolation for frame rate up-conversion

Dabo Guo, Ling Shao, Jungong Han

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

In this paper, we propose to use feature point matching and mesh-based motion estimation for frame rate up-conversion. Matched local feature points between successive frames in a video sequence are employed to constitute a discrete and sparse motion field. Afterwards, a proximity-constraint marking process regulates the raw correspondence set to a content/motion adaptive nodal set. These correspondences are organized by a Delaunay triangular mesh so as to generate a dense motion field through the affine transformation. The experimental results demonstrate that the proposed scheme outperforms three other popular methods in terms of both subjective and objective evaluations. They also suggest that the proposed method is more suitable for videos containing a complex motion field.
Original languageEnglish
Pages (from-to)390-397
JournalNeurocomputing
Volume123
DOIs
Publication statusPublished - 10 Jan 2014

Fingerprint

Dive into the research topics of 'Feature-based motion compensated interpolation for frame rate up-conversion'. Together they form a unique fingerprint.

Cite this