Learning to automatically spectate games for Esports using object detection mechanism

作者：

Highlights：

• The observer who selects engaging scenes is a vital part of Esports.

• The paper proposes an automatic observer model based on human observational data.

• Our proposed method focuses on a two-dimensional spatial area the spectator watches.

• The proposed model applied an object detection mechanism to find the spatial area.

• The proposed model has higher performance than the existing event-based method.

摘要

•The observer who selects engaging scenes is a vital part of Esports.•The paper proposes an automatic observer model based on human observational data.•Our proposed method focuses on a two-dimensional spatial area the spectator watches.•The proposed model applied an object detection mechanism to find the spatial area.•The proposed model has higher performance than the existing event-based method.

论文关键词：Esports,Spectators,Automatic observer,Mask R-CNN,StarCraft

论文评审过程：Received 25 July 2022, Revised 30 September 2022, Accepted 3 October 2022, Available online 10 October 2022, Version of Record 21 October 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118979