At present,there are problems with low accuracy in feature extraction of gesture key points in complex background environments.In order to solve the problems existing in traditional methods,a multimodal gesture key point feature extraction algorithm research is proposed in complex environments.Firstly,the gesture image is enhanced by improving the bacterial foraging(BFO)optimization algorithm;Secondly,background removal is performed on gesture images through conditional generation of adversarial networks;Finally,the GIFT method is used to detect the key points of the gesture image,and the multimodal gesture key poiti-scale dual tree complex wavelet transform method and Gabor filtering method.The experimental results show that the proposed algorithm has higher accuracy and better performance in extracting gesture key point features.
关键词
改进细菌觅食优化算法/条件生成对抗网络/Gabor滤波器/双树复小波变换/关键点特征提取
Key words
improving bacterial foraging optimization algorithms/conditional generation adversarial network/gabor filter/double tree complex wavelet transform/key point feature extraction
维普
万方数据