MIMOGR:MIMO millimeter wave radar multi-feature dataset for gesture recognition

Radar-based dynamic gesture recognition has a broad prospect in the field of touchless Human-Computer Interaction (HCI) due to its advantages in many aspects such as privacy protection and all-day working. Due to the lack of complete motion direction information, it is difficult to implement existing radar gesture datasets or methods for motion direction sensitive gesture recognition and cross-domain (different users, locations, environments, etc.) recognition tasks. Therefore, this paper constructs a sensitive feature map dataset of RT, DT, ART, ERT and RDT based on the range velocity, altitude and azimuth information of MIMO millimeter wave radar. A total of 7 types of gestures can be collected, namely waving up, waving down, waving left, waving right, waving forward, waving backward, and double-tap. To prepare a realistic dataset, we employ two data collection strategies: collecting gesture samples from various volunteers and collecting gesture data in various scenarios to enrich our sample.