MCFI-BASED ANIMATION TWEENING ALGORITHM

In hand drawn animation, some of animations are created at very low frame rates because of limited budget. A simple technique for increasing frame rates is animation tweening. In fact, most animation tweening applications process only vector objects. And, the important requirement for animation tweening application is user-defined motion trajectories. In this paper we propose a method to fully automate the tweening process for hit-mapped key frames. Our method is based on motion-compensated frame interpolation (MCFI) which is widely used in compression in digital video coding. Motion estimation technique used in this framework is pyramidal iterative Lucas-Kanade optical flow because the common optical flow algorithms (Barron et al.,; Barron et al., 1994; Camus, 1995; Liu et al., 1998; Benoit and Ferric, 1996) can not handle large pixel motions. We propose a newly developed motion-compensated frame interpolation in cooperative with one-to-many relation optical flow field and valid interpolated backward difference vectors. One-to-many relation optical flow field can solve the uncovered regions in case that the objects have large different in shape and size. Valid interpolated backward difference vectors can solve the uncovered regions on the border areas of the image when some objects have first occurrence on the latter key frame. The proposed method can perform better results than classical optical flow based motion-compensated frame interpolation especially on uncovered regions. The aim of this work is to make proposed animation tweening algorithm generates the intermediate frames without requirement of user-defined motion trajectories.