TY - GEN
T1 - Demo Abstract
T2 - 2022 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2022
AU - Chen, Ying
AU - Inaltekin, Hazer
AU - Gorlatova, Maria
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Offloading the computation-intensive virtual reality (VR) frame rendering to the edge server is a promising approach to providing immersive VR experiences in mobile VR devices with limited computational capability and battery lifetime. However, edge-assisted VR systems require the data delivery at a high data rate, which poses challenges to the wireless communication between the edge and the device. In this demo, to reduce the communication resource consumption, we present PixSimVR, a pixel similarity-based content reuse framework for edge-assisted VR. PixSimVR analyzes the similarity of the pixels across different VR frames that correspond to different viewport poses, i.e., users' points of view in the virtual world. Based on the pixel similarity level, PixSimVR adaptively splits the VR content into the foreground and the background, reusing the background that has a higher similarity level across frames. Our demo showcases how PixSimVR reduces bandwidth requirements by adaptive VR content reuse. Demo participants will develop an intuition for the potential of exploiting the correlation between VR frames corresponding to similar viewport poses specifically, and for the promises and the challenges of edge-assisted VR as a whole. This demonstration accompanies [1].
AB - Offloading the computation-intensive virtual reality (VR) frame rendering to the edge server is a promising approach to providing immersive VR experiences in mobile VR devices with limited computational capability and battery lifetime. However, edge-assisted VR systems require the data delivery at a high data rate, which poses challenges to the wireless communication between the edge and the device. In this demo, to reduce the communication resource consumption, we present PixSimVR, a pixel similarity-based content reuse framework for edge-assisted VR. PixSimVR analyzes the similarity of the pixels across different VR frames that correspond to different viewport poses, i.e., users' points of view in the virtual world. Based on the pixel similarity level, PixSimVR adaptively splits the VR content into the foreground and the background, reusing the background that has a higher similarity level across frames. Our demo showcases how PixSimVR reduces bandwidth requirements by adaptive VR content reuse. Demo participants will develop an intuition for the potential of exploiting the correlation between VR frames corresponding to similar viewport poses specifically, and for the promises and the challenges of edge-assisted VR as a whole. This demonstration accompanies [1].
UR - https://www.scopus.com/pages/publications/85133900635
UR - https://www.scopus.com/pages/publications/85133900635#tab=citedBy
U2 - 10.1109/INFOCOMWKSHPS54753.2022.9797972
DO - 10.1109/INFOCOMWKSHPS54753.2022.9797972
M3 - Conference contribution
AN - SCOPUS:85133900635
T3 - INFOCOM WKSHPS 2022 - IEEE Conference on Computer Communications Workshops
BT - INFOCOM WKSHPS 2022 - IEEE Conference on Computer Communications Workshops
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 2 May 2022 through 5 May 2022
ER -