Live360: Viewport-Aware Transmission Optimization in Live 360-Degree Video Streaming

Chen, Jinyu; Luo, Zhenxiao; Wang, Zelong; Hu, Miao; Wu, Di

doi:10.1109/tbc.2023.3234405

Cited by 20 publications

(3 citation statements)

References 45 publications

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“…The authors highlight limitations such as bandwidth constraints when there are multiple sensory devices to be synchronized at the same time with the 360 • videos. Authors in [18], [19] also affirm that playback of 360 • content in high quality can cause network latency due to limitations in bandwidth. Adaptive network mechanisms are identified as potential solutions for 360 • video content streaming, however the compression of video content and decrease in video resolution can negatively impact users' QoE levels [20], [21].…”

Section: Related Workmentioning

confidence: 93%

OmniScent: An Omnidirectional Olfaction-Enhanced Virtual Reality 360° Video Delivery Solution for Increasing Viewer Quality of Experience

Simiscuka,

Ghadge,

Muntean

2023

IEEE Trans. on Broadcast.

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The introduction of multiple sensorial effects to improve viewer multimedia experiences has resulted in the novel field coined mulsemedia. Virtual Reality (VR) is one of the recent enabling technologies for mulsemedia distribution and solutions can be enhanced to include scent dispensers, haptic devices and other equipment, for creation of immersive user experiences. In the past, a number of research works and real-life implementations have integrated smells and visual media. However, the scents are generated from a single location around a user, which can be inaccurate in the case of 360 • VR experiences. This paper presents the architecture, principle, implementation and a feasibility study for OmniScent, an omnidirectional olfaction-enhanced VR 360 • video delivery solution. The approach integrates four olfaction devices placed around a user, integrated with 360 • videos. Scents are released during the video playout in the same direction the related objects appear in the video (e.g., front, back, left or right). An omnidirectional olfaction-enhanced video player was implemented using the WebXR technology, allowing the videos to be seen on both Web browsers and VR headsets. User testing demonstrated that over 70% of experiment participants noticed that the diverse scents, including apple and spices, were presented from multiple directions. Performance tests in terms of Round Trip Time (RTT) and resource consumption indicate that the solution performs well in commercial PC setups.

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Section: Related Workmentioning

confidence: 93%

OmniScent: An Omnidirectional Olfaction-Enhanced Virtual Reality 360° Video Delivery Solution for Increasing Viewer Quality of Experience

Simiscuka,

Ghadge,

Muntean

2023

IEEE Trans. on Broadcast.

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“…Their objective was to minimize the video distortion displayed in the user's viewport within a given transmission capacity. For live streaming, Chen et al [190] segregated the transmission tasks for upstream and downstream, optimizing them asynchronously. Wang et al [191] studied a framework that significantly reduces the uplink bandwidth consumption without compromising the QoE.…”

Section: Adaptive Bitratementioning

confidence: 99%

A Survey on Video Streaming for Next-Generation Vehicular Networks

Huang,

Cheng,

Lien

et al. 2024

Electronics

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As assisted driving technology advances and vehicle entertainment systems rapidly develop, future vehicles will become mobile cinemas, where passengers can use various multimedia applications in the car. In recent years, the progress in multimedia technology has given rise to immersive video experiences. In addition to conventional 2D videos, 360° videos are gaining popularity, and volumetric videos, which can offer users a better immersive experience, have been discussed. However, these applications place high demands on network capabilities, leading to a dependence on next-generation wireless communication technology to address network bottlenecks. Therefore, this study provides an exhaustive overview of the latest advancements in video streaming over vehicular networks. First, we introduce related work and background knowledge, and provide an overview of recent developments in vehicular networking and video types. Next, we detail various video processing technologies, including the latest released standards. Detailed explanations are provided for network strategies and wireless communication technologies that can optimize video transmission in vehicular networks, paying special attention to the relevant literature regarding the current development of 6G technology that is applied to vehicle communication. Finally, we proposed future research directions and challenges. Building upon the technologies introduced in this paper and considering diverse applications, we suggest a suitable vehicular network architecture for next-generation video transmission.

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“…These contributions reflect the ongoing efforts to tackle the diverse challenges in video streaming, ranging from processing complexities to power consumption concerns. Emerging research in the field, such as the study by Avanzato et al [45,51,52] on enhancing video quality in drone communications using VPN bonding, and the work of Lee et al [47] on space-time subsampled video quality, offer new perspectives and future directions for the video streaming industry operations.…”

Section: Literature Review Of Existing Streaming Modelsmentioning

confidence: 99%

DLLBVS: Design of a High-Efficiency Deep Learning based Low-BER Video Streaming Model for High-Noise Wireless Networks

Gowrishankar S., Ramesh Babu H. S, Prasad G. R.

2024

jes

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Design of video streaming models for high-noise networks is a multimodal process that requires efficient channel modelling, noise analysis, error-specific stream control, intelligent data augmentation, etc. This article proposes design of a high-efficiency deep learning based low-BER (Bit Error Rate) Video streaming model for high-noise wireless networks. The proposed model initially uses a Long-Short-Term Memory (LSTM) block for estimation of frame level features, and then uses Orthogonal Frequency Division Multiple Access (OFDMA) based modulation platform for transmission and reception of processed video frames. The OFDMA model is cascaded with a chaotic communication module, which assists in improving data fidelity under different noise conditions. The chaotic communication module is optimized using Grey Wolf Optimizer (GWO), which assists in setting up its hyperparameters for better efficiency under real-time communication scenarios. Video frames were pre-processed using Dual Neural Networks that assisted in estimation of differential frame information sets. Due to estimation of this differential frame information, streaming speed is improved, which assists in increasing number of frames transmitted per second, thereby improving streaming performance for different video types. This frame information is further processed by an iterative Gated Recurrent Unit (GRU) based VARMAx Model, which assists in predicting frame removal instances, thus assisting in faster & low error communications. The GRU VARMAx Model optimizes data flow, thus reducing congestion and improving throughput. The model was tested under AWGN (Additive While Gaussian Noise), Rayleigh, & Rician channel types, and its efficiency was compared with standard streaming techniques in terms of communication delay, Bit Error Rate, Peak to Average Power Ratio (PAPR), throughput, communication jitter and computational complexity levels. Based on this comparison it was observed that the proposed model showcased 3.5% lower communication delay, 8.3% lower BER, 5.9% lower PAPR, 10.5% higher throughput, 3.9% lower jitter and 6.4% lower computational complexity, which makes it highly useful for a wide variety of real-time streaming scenarios.

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Live360: Viewport-Aware Transmission Optimization in Live 360-Degree Video Streaming

Cited by 20 publications

References 45 publications

OmniScent: An Omnidirectional Olfaction-Enhanced Virtual Reality 360° Video Delivery Solution for Increasing Viewer Quality of Experience

OmniScent: An Omnidirectional Olfaction-Enhanced Virtual Reality 360° Video Delivery Solution for Increasing Viewer Quality of Experience

A Survey on Video Streaming for Next-Generation Vehicular Networks

DLLBVS: Design of a High-Efficiency Deep Learning based Low-BER Video Streaming Model for High-Noise Wireless Networks

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