Smoothness Constraints in Recursive Search Motion Estimation for Picture Rate Conversion

Abstract

Abstract-Many motion compensation algorithms are based on block matching. The quality of the block correlation depends on the validity of the brightness constancy assumption and the assumption of fixed translational motion within a block. These assumptions are invalid in areas with texture changes, noise, lighting changes, and rapid deformations. Smoothness priors should enforce stable estimates in these regions by propagating neighboring estimates, while preserving hard object boundaries (piecewise smoothness). Most motion estimation algorithms that successfully implement these constraints are computationally complex. In this paper, we show an intuitive and computationally efficient way to implement them within the framework of (realtime) recursive search, targeting consumer-market embedded devices with limited resources.

[Paper] A Study on Motion Estimation using Block Matching for Spatially Periodic Patterns

“…"Lace" is a panning sequence synthesized from a high resolution still picture, which moves at (6.4, 0) pixels per frame. ), JM PMV ('PMV') 10) , pyramidal implementation of the Lucas-Kanade ('PLK') 8) , Bartels PIII ('BT3') 12) and MDP-flow2 ('MDP') 13) . In the case of QPEL and B&T, FS is performed in the up-sampled image for better precision comparing to two-step search (sub-pixel search follows full-pel search).…”

Perception-Oriented Methodology for Robust Motion Estimation Design

“…Similarly, [1], [2], [5]- [7] recognize that accurate predictions at a highest possible consistency are necessary for a satisfactory viewing experience. Relevant metrics addressing the prediction accuracy, temporal continuity and spatial consistency of the motion vectors are documented in [1], [2], [5]- [7].…”

“…Relevant metrics addressing the prediction accuracy, temporal continuity and spatial consistency of the motion vectors are documented in [1], [2], [5]- [7]. The prediction accuracy and temporal continuity are quantitatively assessed with the 'M2SE' [2], [7], (1) and the spatial inconsistency measure 'SI' based on [7], (2) where and are the image height and width in pixels, respectively, is the set of all the pixels in the entire image, the luminance of the original image at position and at the temporal position .…”

A parallel true motion estimation method based on binarized cross correlation

“…These are usually a combination of correlation methods and smoothness constraints. The main approaches can be classified into three categories, namely optical flow (OF) methods [2]- [4], phase correlation (PC) methods [12]- [15] and block based techniques with recursive search (RS) [5]- [10]. PC methods compute the shift between two image blocks by means of a linear phase term in the Fourier domain [12].…”