An improved active shape model for underground face tracking
ZHANG Xiuqin
WANG Rong
ZHANG Yingjun
Abstract：For low accuracy of face tracking applying active shape model(ASM) in condition of sudden change of illumination and contaminated and covered miner face in underground coal mine,an improved ASM was proposed.Firstly,mirror sample set is formed by definition of mirror image with selected special training sample set.Then,the mirror sample set is processed by logarithmic scale.Finally,related block model is used as ASM learning model for training.The experimental results show that the method can effectively improve accuracy of underground face tracking.
Keywords：underground coal mineface trackingactive shape model
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 53-56 )