Real-Time Scent Generation for Video Games

Abstract

This thesis presents a versatile software framework designed to incorporate olfactory stimuli into interactive gaming environments, exemplified through its application in Minecraft. Our approach leverages recent advancements in wearable scent-release technology and cross-modal machine learning, focusing on an adaptable scent predicting and releasing framework with a customizable pipeline, allowing precise configuration and troubleshooting tailored to different gaming contexts. A quantitative user study was conducted to assess the system’s impact, comparing an optimized scent integration against a randomized scent-integrated experience. Results indicate a significant enhancement in the immersive gaming experience under the optimized configuration, emphasizing the importance of contextually aligned olfactory stimuli, confirming the effectiveness of our system.

This thesis was published at the 30th ACM Symposium on Virtual Reality Software and Technology. View the paper and the accompanying poster in the ETH Research Collection

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