The invention discloses a
human motion tracking method based on a deep nuclear information image feature. The
human motion tracking method based on the deep nuclear information image feature mainly solves the problems that in
human motion tracking of the prior art, features of a
video image are not accurately expressed, so that a tracking result is caused to be not accurate. The method comprising the steps: obtaining an articulation point three-dimensional coordinate matrix Y of the
video image from a
data bank; extracting the deep nuclear information image feature X of the processed
video image; serving the deep nuclear information image feature X as an input, serving the three-dimensional coordinate matrix Y, in the video image, of a
human body as an output, and learning a regression function by using of
gaussian process; learning an obtained regression function by using of the
gaussian process, serving a new deep nuclear information image feature X of the video image as an input, and estimating data of three-dimensional poses of a
moving body. Compared with an existing
human body tracking method, the human motion tracking method based on the deep nuclear information image feature has the advantages of being high in training speed, accurate in express of image features, and capable of being used in motion catching, human-computer interaction, video surveillance, recognition of
human body goals and restoration of the three-dimensional poses.