October 2022
Dr. Ravi Kiran Sarvadevabhatla and his students presented a paper on DrawMon: A Distributed System for Detection of Atypical Sketch Content in Concurrent Pictionary Games at ACM International Conference on Multimedia (ACMMM-2022) held at Lisbon, Portugal from 10 – 14 October.
Research work as explained by the authors of this paper Nikhil Bansal, Kartik Gupta, Kiruthika Kannan, Sivani Pentapati, Ravi Kiran Sarvadevabhatla:
Pictionary, the popular sketch-based guessing game, provides an opportunity to analyze shared goal cooperative game play in restricted communication settings. However, some players occasionally draw atypical sketch content. While such content is occasionally relevant in the game context, it sometimes represents a rule violation and impairs the game experience. To address such situations in a timely and scalable manner, we introduce DrawMon, a novel distributed framework for automatic detection of atypical sketch content in concurrently occurring Pictionary game sessions. We build specialized online interfaces to collect game session data and annotate atypical sketch content, resulting in AtyPict, the first ever atypical sketch content dataset. We use AtyPict to train CanvasNet, a deep neural atypical content detection network. We utilize CanvasNet as a core component of DrawMon. Our analysis of post deployment game session data indicates DrawMon’s effectiveness for scalable monitoring and atypical sketch content detection. Beyond Pictionary, our contributions also serve as a design guide for customized atypical content response systems involving shared and interactive whiteboards.
PDF of the paper: https://rebrand.ly/drawmon-pdf
Project page: https://drawm0n.github.io/
Conference page: https://2022.acmmm.org/