A novel projection for omni-directional video

Abbas, Adeel; Newman, D. L.

doi:10.1117/12.2271944

Cited by 8 publications

(4 citation statements)

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“…There are many ways to project panoramic video [26], such as equirectangular projection (ERP) [27], cylindrical equalarea projection (EAP) [27], cube map projection (CMP) [28], rotated sphere projection (RSP) [29], etc. In respective of the method to use, it will inevitably distort the original pixel distribution and shape.…”

Section: A Spatial Domain Characteristics Of Panoramic Videomentioning

confidence: 99%

Panoramic Video Quality Assessment Based on Non-Local Spherical CNN

Yang

Liu

Jiang

et al. 2021

IEEE Trans. Multimedia

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Panoramic video and stereoscopic panoramic video are essential carriers of virtual reality content, so it is very crucial to establish their quality assessment models for the standardization of virtual reality industry. However, it is very challenging to evaluate the quality of the panoramic video at present. One reason is that the spatial information of the panoramic video is warped due to the projection process, and the conventional video quality assessment (VQA) method is difficult to deal with this problem. Another reason is that the traditional VQA method is problematic to capture the complex global time information in the panoramic video. In response to the above questions, this paper presents an end-to-end neural network model to evaluate the quality of panoramic video and stereoscopic panoramic video. Compared to other panoramic video quality assessment methods, our proposed method combines spherical convolutional neural networks (CNN) and non-local neural networks, which can effectively extract complex spatiotemporal information of the panoramic video. We evaluate the method in two databases, VRQ-TJU and VR-VQA48. Experiments show the effectiveness of different modules in our method, and our method outperforms state-of-the-art other related methods.

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Section: A Spatial Domain Characteristics Of Panoramic Videomentioning

confidence: 99%

Panoramic Video Quality Assessment Based on Non-Local Spherical CNN

Yang

Liu

Jiang

et al. 2021

IEEE Trans. Multimedia

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“…Various projection methods have been proposed recently to address these problems by trying to reduce the number of pixels without deteriorating the user's quality of experience (QoE). Notable examples include cubemap projection (CMP) [28], pyramid projection (PMP) [29], icosahedral projection (ISP) [30], segmented sphere projection (SSP) [31], and rotated sphere projection (RSP) [32].…”

Section: ) 360-degree Videomentioning

confidence: 99%

Fog Computing as an Enabler for Immersive Media: Service Scenarios and Research Opportunities

et al. 2019

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Immersive media services, such as augmented reality and virtual reality (AR/VR), a 360degree video, and free-viewpoint video (FVV), are popular today. They require massive data storage, ultrahigh computing power, and ultralow latency. It is hard to fulfill these requirements simultaneously in a conventional communication system using a cloud/centralized radio access network (C-RAN). Specifically, due to centralized processing in such a system, the end-to-end latency, as well as the burden on the fronthaul network, are expected to be high. Fog computing-based radio access networks (F-RAN), in contrast, have been widely considered as an enabler for immersive media. Our contribution in this paper is threefold: First, we propose various service scenarios reflecting the characteristics of immersive media. Second, we identify the technologies that are required to support the proposed service scenarios under F-RAN and discuss how they can support the proposed scenarios efficiently. Third, we discuss possible research opportunities.a A list of acronyms can be found in the Appendix.INDEX TERMS Fog computing, radio access networks, immersive media, free-viewpoint video, 360-degree video, virtual reality, augmented reality.

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“…This can be performed by means of a projection format. To this end, many projection formats have been proposed and developed in the literature [10]. In the following, some of the projection formats included in the 360Lib package [7], which are used in this work, are discussed:…”

Section: A Projectionsmentioning

confidence: 99%

Comparison of 3D 360-Degree Video Compression Performance Using Different Projections

Jamali

Golaghazadeh

Coulombe

et al. 2019

2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE)

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3D and multi-view 360-degree videos offer 3D immersive visual experience of the real world on head-mounted displays (HMDs). They are used in extended reality applications (including virtual reality, augmented reality and mixed reality) such as gaming, entertainment, education and medicine. However, these applications require a very high rate of compression and a great deal of computational resources. Compression efficiency and coding complexity are highly influenced by 360 projections used to map spherical frames to rectangular frames. To study the effect of this mapping process, in this paper, we evaluate the performance of various projections in 3D and multi-view 360-degree videos in terms of coding efficiency, quality and complexity. The evaluation is conducted for two coding scenarios: stereo coding scenario where the encoder considers the interview dependency for disparity estimation and simulcast coding scenario where two views are encoded separately. This performance evaluation approach provides valuable insights on using 360-degree projections in 3D and multi-view coding.

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A novel projection for omni-directional video

Cited by 8 publications

References 0 publications

Panoramic Video Quality Assessment Based on Non-Local Spherical CNN

Panoramic Video Quality Assessment Based on Non-Local Spherical CNN

Fog Computing as an Enabler for Immersive Media: Service Scenarios and Research Opportunities

Comparison of 3D 360-Degree Video Compression Performance Using Different Projections

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