Computer Vision - ECCV 2014 Workshops

Volume 8925 of the series Lecture Notes in Computer Science pp 698-712


G3Di: A Gaming Interaction Dataset with a Real Time Detection and Evaluation Framework

  • Victoria BloomAffiliated withKingston University Email author 
  • , Vasileios ArgyriouAffiliated withKingston University
  • , Dimitrios MakrisAffiliated withKingston University


This paper presents a new, realistic and challenging human interaction dataset for multiplayer gaming, containing synchronised colour, depth and skeleton data. In contrast to existing datasets where the interactions are scripted, G3Di was captured using a novel gamesourcing method so the movements are more realistic. Our detection framework decomposes interactions into the actions of each person to infer the interaction in real time. This modular approach is applicable to a virtual environment where the interaction between people occurs through a computer interface. We also propose an evaluation metric for real time applications, which assesses both the accuracy and latency of the interactions. Experimental results indicate higher complexity of the new dataset in comparison to existing gaming datasets.


Human interaction recognition Multimodal dataset Multiplayer gaming Interaction evaluation metric