Robust Motion Estimation Design Methodology

Abstract

For motion-adaptive video retiming methods, the quest to lower the implementation complexity and improve the quality of motion estimation algorithms still continues. Comparing different motion estimators (MEs) and/or fine-tuning ME parameters is a time-consuming task, and it is even more demanding to identify the MEs with a robust performance among all the well-performing MEs. Therefore, a computer-aided design methodology is required to effectively explore the large design space. Such a methodology requires objective performance metrics. As it is hard to find perfect metrics, we present a design methodology that can use suboptimal measures and still identify robust MEs. The proposed methodology is demonstrated using two different MEs.

Perception-Oriented Methodology for Robust Motion Estimation Design

“…The 93 MEs were systematically selected from a total of 7000 ME alternatives. The current paper can be seen as an extension of earlier work described in [8] and [9]. The proposed methodology may provide an inspiration for similar tough multi-dimensional optimization tasks with unreliable metrics.…”

“…Significance is judged when the -value .05. denotes the -value for sequence where . For partition 2 (attractive segment as defined in [9]), a significantly higher mean score on quality was obtained than for the other MEs in the sequence: , , . The difference between partition 3 (high PSNR influence) and the rest of the quality scores appeared to be significant too:…”

“…They differ in position and size in the 1/PSNR-Inconsistency plot. The first partition is limited to the contour line, the second partition describes the attractive segment proposed in [9], and the third partition is biased to high PSNR scores, largely disregarding the SI score. This bias is chosen to assess the influence of the PSNR and SI measures on the perceived video quality.…”

“…In Section II, we present the proposed robust ME design methodology followed by video data analysis results on ten test sequences supporting the robustness claims made in [8] and [9]. Section III describes the user perception test to confirm and improve the proposed design methodology.…”