Many stereoscopic image retargeting (SIR) methods have been developed for automatically and intelligently resizing stereoscopic images and we cannot always rely on time-consuming subjective user studies to validate the performance of different SIR methods. It is therefore required to design reliable objective metrics for SIR quality evaluation. This paper extends our previous 2D aspect ratio similarity (ARS) metric to a stereo 3D version termed as StereoARS where the key idea is to investigate into retargeting inconsistency between the original stereo correspondences. Our proposed StereoARS operates via two stages: monocular quality estimation and binocular inconsistency detection. In the first stage, monocular quality estimation is performed by applying a modified ARS measure on the left and right views separately to quantify the quality degradation within each monocular view. In the second stage, binocular inconsistency detection is performed in both pixel-level and grid-level to characterize the influence of binocular rivalry and stereo visual discomfort on SIR quality. In addition, we also measure to what extent the original pixel visibility relation is preserved after SIR as another binocular quality factor. Finally, these monocular and binocular quality estimates are fused to produce an overall SIR quality score. Extensive experiments have demonstrated that StereoARS achieves better alignment with human subjective ratings than the existing metrics by a large margin.

中文翻译：

---

StereoARS：双目不一致检测立体图像重定位的质量评估

许多立体图像重定向 (SIR) 方法已被开发用于自动和智能地调整立体图像的大小，我们不能总是依赖耗时的主观用户研究来验证不同 SIR 方法的性能。因此，需要为 SIR 质量评估设计可靠的客观指标。本文将我们之前的 2D 纵横比相似度 (ARS) 度量扩展为立体 3D 版本，称为StereoARS 的关键思想是调查原始立体对应之间的重定向不一致。我们提出的StereoARS 通过两个阶段进行操作：单目质量估计和双目不一致检测。在第一阶段，通过分别对左右视图应用修改后的 ARS 测量来执行单目质量估计，以量化每个单目视图内的质量下降。在第二阶段，在像素级和网格级进行双眼不一致性检测，以表征双眼竞争和立体视觉不适对 SIR 质量的影响。此外，我们还测量了在 SIR 作为另一个双目品质因素之后，原始像素可见性关系在多大程度上得以保留。最后，这些单目和双目质量估计被融合以产生整体 SIR 质量得分。大量实验表明，StereoARS 与现有指标相比，在很大程度上实现了与人类主观评级的更好一致性。