提出了一种以人的动作序列图像的轮廓为特征，基于RBF神经网络的日常行为识别方法。
RBF neural network-based method for action recognition is presented by using the contours of image sequence as representative descriptors of human posture to achieve daily human actions recognition.
提出了一种以人的动作序列图像的轮廓为特征，基于RBF神经网络的日常行为识别方法。
A RBF neural network-based method for action recognition is presented by using the contours of image sequence as representative descriptors of human posture to achieve daily human actions recognition.
对运动人手序列图像的对比跟踪实验表明，这种融合使得可见光图像中动态轮廓线平均跟踪误差减小了60.25%。
A contrasting experiment on moving hand image sequence indicates average tracking error of dynamic contour has decreased by 60.25% in visible image with this image fusion.
应用推荐