The next generation of smart sensors is coming…
RadarCat (Radar Categorization for Input & Interaction) is a small, versatile radar-based system for material and object classification which enables new forms of everyday proximate interaction with digital devices. In this work we demonstrate that we can train and classify different types of objects which we can then recognize in real time. Our studies include everyday objects and materials, transparent materials and different body parts. Our videos demonstrate four working examples including a physical object dictionary, painting and photo editing application, body shortcuts and automatic refill based on RadarCat.
Beyond human computer interaction, RadarCat also opens up new opportunities in areas such as navigation and world knowledge (e.g., low vision users), consumer interaction (e.g., checkout scales), industrial automation (e.g., recycling), or laboratory process control (e.g., traceability).