Human Chest and Waist Detection Based on Deep Learning

Updated: 11/25/2020 10:17:03 AM

Abstract: The paper proposes a deep learning method to perform target detection on human chest and waist images. First, select and fine-tune the SSD (Single Shot MultiBox Detector) target detection algorithm model. Second, use the male body image to train the algorithm model. Finally, use the trained model to identify and locate the human chest and waist. Compared with the training speed and accuracy of the Mask-RCNN algorithm model, results showed that although the Mask-RCNN algorithm model runs faster, the SSD target detection algorithm can relatively accurately identify and locate the human chest and waist, and the detection accuracy reaches 91.6%. This can improve the accuracy of the size of the human chest and waist in the remote online tailor-made.

Key words: deep learning; SSD algorithm; Mask-RCNN algorithm; positioning and recognition; chest and waist; online tailoring

Authority in Charge: China National Textile and Apparel Council (CNTAC)

Sponsor :China Textile Information Center (CTIC)

ISSN 1003-3025 CN11-1714/TS