Human Action Recognition Based on Global Silhouette and Local Optical Flow
Ning Zhang, Zeyuan Hu, Sukhwan Lee, Eung‐Joo Lee · 2018
Currently, Human Activity Recognition is a research hotspot in the field of machine vision, it involves knowledge of image processing, pattern recognition, artificial intelligence and many other disciplines.Video-based Human Activity Recognition including human area detection, movement and gesture segmentation, objective analysis and behavior understands for activity recognition and so on.In the past, the behavior recognition technology based on the single characteristic was too restrictive, in this paper, we proposed a mixed feature which combined global silhouette feature and local optical flow feature, and this combined representation was used for human action recognition.In the end, test the model with other samples from the database.