TY - GEN
T1 - Crowd-sourced Evaluation of Combat Animations
AU - Zhang, Yunhao
AU - Weiss, Tomer
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Combat sequences are commonly seen in films, animated media, and video games. Although significant advancements have led to the creation of extensive online collections of these animations, selecting suitable motions for specific uses remains challenging because of their dynamic characteristics. This dynamism and perceptual complexity stem from stylized combat scenes' diverse physical and aesthetic elements. This paper introduces a novel methodology to comprehend user preferences in combat animations with a crowd-sourced learning strategy. We deduce user preferences towards certain motion attributes, which are not easily identifiable through raw geometric data. Our study primarily focuses on sword fighting, which is widely popular in combat scenes.
AB - Combat sequences are commonly seen in films, animated media, and video games. Although significant advancements have led to the creation of extensive online collections of these animations, selecting suitable motions for specific uses remains challenging because of their dynamic characteristics. This dynamism and perceptual complexity stem from stylized combat scenes' diverse physical and aesthetic elements. This paper introduces a novel methodology to comprehend user preferences in combat animations with a crowd-sourced learning strategy. We deduce user preferences towards certain motion attributes, which are not easily identifiable through raw geometric data. Our study primarily focuses on sword fighting, which is widely popular in combat scenes.
KW - animation
KW - statistical learning
UR - http://www.scopus.com/inward/record.url?scp=85187214317&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85187214317&partnerID=8YFLogxK
U2 - 10.1109/AIxVR59861.2024.00015
DO - 10.1109/AIxVR59861.2024.00015
M3 - Conference contribution
AN - SCOPUS:85187214317
T3 - Proceedings - 2024 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality, AIxVR 2024
SP - 60
EP - 65
BT - Proceedings - 2024 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality, AIxVR 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality, AIxVR 2024
Y2 - 17 January 2024 through 19 January 2024
ER -