Gait analysis and recognition prediction of the human skeleton based on migration learning

Gait recognition is a hot topic in the computing. Different gaits have different characteristics. This paper predicts whether a person in an image or video is running or walking by capturing the behavior of a character in an image or video. In this paper, we identify the gait by adopting the method of transfer learning and inception -V3 neural network. At the same time, the paper uses the HMDB - a large human motion database and UCF sports actions video action data as the main data set. At the end, this will help predict if the characters in either the picture or video make a running or walking motion. Results show a significant increase in object detection performance in comparison to existing algorithms with the use of transfer learning neural networks adapted for mobile use. (C) 2019 Elsevier B.V. All rights reserved.