TY - GEN
T1 - Live Free-View Video for Soccer Games
AU - Amar, Islam
AU - Elsana, Abdalla
AU - El-Sana, Jihad
N1 - Publisher Copyright: © 2023 Owner/Author.
PY - 2023/10/9
Y1 - 2023/10/9
N2 - Free-view video lets viewers choose their camera parameters when watching a recorded or live event; they can interactively control the camera view and choose to focus on different parts of the scene. This paper presents a novel client-server architecture approach for free-view videos of sports. The clients obtain a detailed 3D representation of the players and the game field from the server of a shared repository. The server receives video streams from several cameras around the game field, detects the players, determines the camera with the best view, extracts the poses of each player, and encodes this data with a timestamp into a snapshot, which is streamed to the clients. A client receives a stream of snapshots, applies each pose to the appropriate player's 3D model (avatar), and renders the scene according to the user's virtual camera. We have implemented our approach while using VIBE [Kocabas et al. 2020] for pose extraction and obtained promising results. We transferred a soccer game into a 3D representation supporting free-view with a reconstruction error below . Our unoptimized implementation is nearly real-time; it runs at about 30 frames/second.
AB - Free-view video lets viewers choose their camera parameters when watching a recorded or live event; they can interactively control the camera view and choose to focus on different parts of the scene. This paper presents a novel client-server architecture approach for free-view videos of sports. The clients obtain a detailed 3D representation of the players and the game field from the server of a shared repository. The server receives video streams from several cameras around the game field, detects the players, determines the camera with the best view, extracts the poses of each player, and encodes this data with a timestamp into a snapshot, which is streamed to the clients. A client receives a stream of snapshots, applies each pose to the appropriate player's 3D model (avatar), and renders the scene according to the user's virtual camera. We have implemented our approach while using VIBE [Kocabas et al. 2020] for pose extraction and obtained promising results. We transferred a soccer game into a 3D representation supporting free-view with a reconstruction error below . Our unoptimized implementation is nearly real-time; it runs at about 30 frames/second.
KW - Human Body Animation
KW - Human Body Reconstruction
KW - Sports Real-time Rendering
UR - http://www.scopus.com/inward/record.url?scp=85175444075&partnerID=8YFLogxK
U2 - https://doi.org/10.1145/3611314.3615922
DO - https://doi.org/10.1145/3611314.3615922
M3 - Conference contribution
T3 - Proceedings - Web3D 2023: 28th International Conference on Web3D Technology
BT - Proceedings - Web3D 2023
A2 - Spencer, Stephen N.
T2 - 28th International Conference on Web3D Technology, Web3D 2023
Y2 - 9 October 2023 through 11 October 2023
ER -