Hand Gesture Recognition
Hand Gesture Recognition (HGR) engine provides the functions of registering hand gestures for Grayscale/IR video input and recognizing them.
It receives video images from a camera or a file-based video image data saved in the storage device, and delivers the results to the application.
It can recognize hand gestures, receive the configuration information of the video data from the input data, and use them for analyzing the video data.
The HGR engine provided by ThinQ.AI supports the following features:
|Few-shot gesture control||
Learns gestures from 1 to 3 second-long short videos (learning with few-shot samples).
It allows operating on a low-power CPU for deep-learning-based hand-gesture recognition (Raspberry Pi 4).
|DNN based pipeline||
Through the DNN-based pipeline, it can track the palm and hand skeleton to classify hand gestures.
HGR engine receives video image data as an input, recognizes hand gestures, and outputs the result.
Examples of Use
It can be applied to various services with an embedded camera.
- You can use it for gesture recognition by installing it in a smart camera, XR device, signage, or home appliance.
- You can increase the proportion of non-contact diagnosis or treatment by applying it to health care.
- You can reduce the risk of injury by applying it to the manufacturing process and minimizing the number of direct contact.