Perceptual quality assessment of panoramic stitched contents for immersive applications:a prospective survey

作     者：Hayat ULLAH Sitara AFZAL Imran Ullah KHAN 

作者机构：Department of Computer ScienceKansas State UniversityManhattanKS 66506USA Department of SoftwareSejong UniversitySeoul 143-747Republic of Korea 

出 版 物：《Virtual Reality & Intelligent Hardware》 (虚拟现实与智能硬件（中英文）)

年 卷 期：2022年第4卷第3期

页      面：223-246页

核心收录：

学科分类：08[工学] 080203[工学-机械设计及理论] 0835[工学-软件工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Virtual reality Augmented reality Panoramic image Immersive contents Stitched image quality assessment Deep learning Convolutional neural networks 

摘      要：The recent advancements in the field of Virtual Reality(VR)and Augmented Reality(AR)have a substantial impact on modern day technology by digitizing each and everything related to human life and open the doors to the next generation Software Technology(Soft Tech).VR and AR technology provide astonishing immersive contents with the help of high quality stitched panoramic contents and 360°imagery that widely used in the education,gaming,entertainment,and production *** immersive quality of VR and AR contents are greatly dependent on the perceptual quality of panoramic or 360°images,in fact a minor visual distortion can significantly degrade the overall ***,to ensure the quality of constructed panoramic contents for VR and AR applications,numerous Stitched Image Quality Assessment(SIQA)methods have been proposed to assess the quality of panoramic contents before using in VR and *** this survey,we provide a detailed overview of the SIQA literature and exclusively focus on objective SIQA methods presented till *** better understanding,the objective SIQA methods are classified into two classes namely Full-Reference SIQA and No-Reference SIQA *** class is further categorized into traditional and deep learning-based methods and examined their performance for SIQA ***,we shortlist the publicly available benchmark SIQA datasets and evaluation metrices used for quality assessment of panoramic *** last,we highlight the current challenges in this area based on the existing SIQA methods and suggest future research directions that need to be target for further improvement in SIQA domain.