Stereoscopic Image Retargeting (SIR) has made it possible for the popularity of 3D application. Meanwhile, the adjustments brought to images may affect the visual comfort when enjoying 3D service. While for SIR, previous Visual Comfort Assessment (VCA) methods often cannot perform well, because they only analyze the influence of disparity on discomfort and do not take into account the effects from the unique and complex distortions of SIR. In this paper, we propose a Hierarchical Visual Comfort Assessment (Hi-VCA) scheme for SIR, considering hybrid distortions including structure, information, semantic distortions usually occurring in retargeting, and binocular incongruity existing in stereoscopic multimedia. Specifically, we first propose valid Local-SSIM and Dual Natural Scene Statistics (D-NSS) features to measure structural distortion and information loss. Considering disparity adjustments may brought by SIR, we design the binocular incongruity measurement by analyzing various binocular anomaly perception mechanisms of HVS. Finally, CNN-based feature is utilized to ensure the correct delivery of semantic information. Each measurement is complementary in describing visual comfort degradation and they are further aggregated. Extensive experiment results on published SIR database SIRD and two ordinary databases IEEE-SA and NBU 3D-VCA, demonstrate Hi-VCA has superior performance by better handling hybrid distortions compared to state-of-the-art schemes.

立体图像重定向（SIR）使得3D应用程序的普及成为可能。同时，图像的调整可能会影响享受3D服务时的视觉舒适度。对于SIR，以前的视觉舒适度评估（VCA）方法通常效果不佳，因为它们仅分析视差对不适的影响，而没有考虑SIR独特而复杂的失真的影响。在本文中，我们提出了一种针对SIR的分层视觉舒适度评估（Hi-VCA）方案，其中考虑了混合失真，包括结构，信息，通常在重新定向中出现的语义失真以及立体多媒体中存在的双目不一致性。具体来说，我们首先提出有效的Local-SSIM和Dual Natural Scene Statistics（D-NSS）功能来测量结构变形和信息丢失。考虑到SIR可能带来的视差调整，我们通过分析HVS的各种双眼异常感知机制来设计双眼不一致性测量。最后，基于CNN的功能可用于确保语义信​​息的正确传递。每种度量值在描述视觉舒适度下降时都是互补的，并且会进一步汇总。在已发布的SIR数据库SIRD和两个普通数据库IEEE-SA和NBU 3D-VCA上的大量实验结果表明，与最新方案相比，Hi-VCA通过更好地处理混合失真而具有出色的性能。我们通过分析HVS的各种双眼异常感知机制来设计双眼不一致性测量。最后，基于CNN的功能可用于确保语义信​​息的正确传递。每种度量值在描述视觉舒适度下降时都是互补的，并且会进一步汇总。在已发布的SIR数据库SIRD和两个普通数据库IEEE-SA和NBU 3D-VCA上的大量实验结果表明，与最新方案相比，Hi-VCA通过更好地处理混合失真而具有出色的性能。我们通过分析HVS的各种双眼异常感知机制来设计双眼不一致性测量。最后，基于CNN的功能可用于确保语义信​​息的正确传递。每种度量在描述视觉舒适度下降时都是互补的，并且会进一步汇总。在已发布的SIR数据库SIRD和两个普通数据库IEEE-SA和NBU 3D-VCA上的大量实验结果表明，与最新方案相比，Hi-VCA通过更好地处理混合失真而具有出色的性能。