Hand gesture detection method involves acquiring initial depth image using backbone and apparatus, and non-transitory computer-readable storage medium

A hand gesture detection apparatus, comprising:

• a processor;
• and
• a memory having instructions stored thereon and executable by the processor, wherein the instructions, when executed by the processor, implement a hand gesture detection method comprising:
• obtaining an initial depth image comprising a hand to be detected, and performing detection processing on the initial depth image by using a backbone feature extractor and a bounding box detection model, to obtain initial bounding boxes and a first feature map corresponding to the hand to be detected;
• determining a target bounding box based on the initial bounding boxes, the target bounding box being one of the initial bounding boxes;
• cropping, based on the target bounding box, the first feature map by using an RoIAlign feature extractor, to obtain a second feature map corresponding to the hand to be detected;
• and
• performing, based on the second feature map, a three-dimensional gesture estimation processing on the hand to be detected by using a gesture estimation model to obtain a gesture detection result of the hand to be detected.

A non-transitory computer-readable storage medium, having a program stored thereon and applied to a hand gesture detection apparatus, wherein the program, when executed by a processor, implements a hand gesture detection method comprising:

• obtaining an initial depth image comprising a hand to be detected, and performing detection processing on the initial depth image by using a backbone feature extractor and a bounding box detection model, to obtain initial bounding boxes and a first feature map corresponding to the hand to be detected;
• determining a target bounding box based on the initial bounding boxes, the target bounding box being one of the initial bounding boxes;
• cropping, based on the target bounding box, the first feature map by using an RoIAlign feature extractor, to obtain a second feature map corresponding to the hand to be detected;
• and
• performing, based on the second feature map, a three-dimensional gesture estimation processing on the hand to be detected by using a gesture estimation model to obtain a gesture detection result of the hand to be detected.