Optimization of Human Body Attitude Detection Based on Mask RCNN

Mask RCNN has the advantage of higher accuracy than other human body attitude detection models, and has been widely used for multi-person human body attitude detection. However, Mask RCNN has a low detection speed. Therefore, we propose a MobileNet-based Mask RCNN optimization model to accelerate the inference calculation speed of Mask RCNN. At the same time, in order to further improve the detection accuracy of Mask RCNN, we propose a method by using pixel segmentation results to assist the detection of key points in the human body, which improves the speed of reasoning and reduces the rate of false detection to some extent.