Immersive virtual reality (VR) technology is becoming mainstream. The VR content is usually captured via multi-camera setup or a single camera with multiple lenses. There are many commercially available cameras in the consumer market that can capture high-resolution VR images and videos. Such content is usually consumed through Head-Mounted Display (HMD) devices or a via normal 2D displays.
Nowadays, VR technology is being widely used in many applications such as gaming, live events streaming, medical or training.
“This technology makes use of omnidirectional content in order to create immersion in the virtual environment. Omnidirectional content is captured in a way that it covers the entire 360° field-of-view (FOV) around the capturing device. Thus, it is able to create the three Degrees-of-Freedom (3-DoF) experience in VR. In order to create an immersive experience, VR technology is required to use stereoscopic omnidirectional video in high resolution, quality and frame rates. Such requirements introduce significant challenges in the encoding and streaming stages of this technology,” Ramin Ghaznavi Youvalari says.
In recent years, viewport-adaptive streaming (VAS) methods have been considered for VR applications, instead of traditional streaming, where only the portion of the content that falls into the viewing orientation of the user is transmitted in a high resolution and/or quality, while the remaining parts are streamed in a lower resolution and/or quality.
“Even though these methods improve the streaming performance compared to transmitting the omnidirectional video in the traditional way, they use frequent Intra Random Access Points (IRAPs) for switching from one viewing orientation to another. The IRAP switching points are intra-coded pictures and they consume significantly higher bitrates compared to the inter-coded pictures. In order to have seamless viewport switching in the content, the streaming method must have frequent IRAP pictures. Thus, the frequent IRAPs make the viewport-adaptive streaming operation sub-optimal,” Ghaznavi Youvalari noted.
In his dissertation, Ghaznavi Youvalari investigates and proposes novel streaming methods that enable frequent viewport switching operations without the need for having frequent IRAP pictures in the compressed bitstream of VR content. Thus, the proposed methods provide significant improvements to the existing state-of-the-art viewport-adaptive streaming solutions.
Ramin Ghaznavi Youvalari is originally from Iran and he received his M.Sc. degree in Information Technology from Tampere University of Technology (TUT) in 2016. Currently, he is a senior researcher at Nokia Technologies and his work is focused on developing new image and video compression and streaming methods for future codecs.
The doctoral dissertation of M. Sc. Ramin Ghaznavi Youvalari in the field of signal processing titled Encoding and Streaming Solutions for Immersive Virtual Reality Video will be publicly examined in the Faculty of Information Technology and Communication Sciences of Tampere University at 12 o'clock on Friday 12 February 2021. The Opponent will be Priv. Doz. Dr.-Ing. habil. Mathias Wien from RWTH Aachen University, Germany. The Custos will be Professor Moncef Gabbouj from the Faculty of Information Technology and Communication Sciences of Tampere University.
The event can be followed via remote connection.
The dissertation is available online at http://urn.fi/URN:ISBN:978-952-03-1852-9.
Photo: Nahid Sheikhipour