Cricket is a game that requires players to constantly adapt to situations and customize their game depending on opponents and playing conditions. Players and coaching staff often watch video clips to understand the strategies of opponents. Iterating through multiple matches over many years across various leagues and formats, and extracting clips is a tiring process. In this paper, we propose a computer vision framework to segment cricket matches into clips based on context and construct real-time graphs using meta-data from segmented clips. We discuss various queries on the generated graphs and also evaluate our segmentation and querying model based on the accuracy and quality of the retrieved data. CCS CONCEPTS • Information systems → Multimedia streaming; • Human-centered computing → Visual analytics.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.