Next Generation Frame Rate Conversion Algorithms

Abstract

There is an increasing trend towards panel displays in consumer electronics, and they are already replacing conventional Cathode Ray Tube (CRT) displays due to their various advantages. However, the main problem of the panel displays, namely motion blur, still remains unsolved. This shortcoming should be overcome efficiently to satisfy increasing demands of viewers such as artifact-free interpolation in dynamic videos. Among many frame-rate up conversion (FRUC) methods that address this problem, motion-compensated frame interpolation (MCFI) algorithms yield superior results with relatively less artifacts. Conventional MCFI techniques utilize block-based translational motion models and, in general, linear interpolation schemes. These methods, however, suffer from blocking artifacts especially at object boundaries despite several attempts to avoid them. Region-based methods tackle this problem by segmenting homogeneous, or smoothly varying, motion regions that are supposed to correspond real objects (or their parts) in the scene. In this chapter, two region-based MCFI methods that adopt 2D homography and 3D rigid body motion models are presented in the order of increasing complexity. As opposed to the conventional MCFI approaches where motion model interpolation is performed in the induced 2D motion parameter space, the common idea behind both methods is to perform the interpolation in the parameter space of the original 3D motion and structure elements of the scene. Experimental results suggest that the proposed algorithms achieve visually pleasing results without halo effects on dynamic scenes with complex motion.