Fine Pedestrian Segmentation with Parts Detection and Retrieval
WANG Feng, LI Zhi, LIU Qing-shan, SUN Yu-bao
B-DAT Lab, Collaborative Innovation Center, School of Information & Control, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, China
Abstract：Focused on the diversity of appearance and the complexity of configuration,laying,and occasion in human images,a coarse-to-fine method was proposed for effective human parsing.It can decompose a human image into semantic regions which consists of three phases.In the first two phases,two effective models were trained with Fast Region-based Convolutional Network(Fast R-CNN)to respectively detect human body and clothing items.In the third phase,parsing clothing items based on retrieving similar over-segmented images and morphing them into absolute image coordinates.Experiments are conducted on three public databases,and the experimental results show that proposed method has higher accuracy and promising performance.
王枫, 厉智, 刘青山, 孙玉宝. 基于部件检测与检索的行人精细化分割[J]. 电子学报, 2019, 47(2): 502-508.
WANG Feng, LI Zhi, LIU Qing-shan, SUN Yu-bao. Fine Pedestrian Segmentation with Parts Detection and Retrieval. Acta Electronica Sinica, 2019, 47(2): 502-508.
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2019, Vol. 47 
