Recognizing hand gestures using the weighted elastic graph matching (WEGM) method

作者:

Highlights:

• The HEGM method for classifying hand postures with a hit rate of 97.08% on average over uniform and complex backgrounds.

• This method allows computing only features corresponding to highly discriminative nodes, thus decreasing computing time.

• A semi-automatic technique to annotate bunch graphs is described which is efficient and leads to faster graph creation.

摘要

•The HEGM method for classifying hand postures with a hit rate of 97.08% on average over uniform and complex backgrounds.•This method allows computing only features corresponding to highly discriminative nodes, thus decreasing computing time.•A semi-automatic technique to annotate bunch graphs is described which is efficient and leads to faster graph creation.

论文关键词:Elastic bunch graph,Graph matching,Feature weight,Hand gesture recognition

论文评审过程:Received 26 June 2012, Revised 24 March 2013, Accepted 19 June 2013, Available online 3 July 2013.

论文官网地址:https://doi.org/10.1016/j.imavis.2013.06.008