Activity Recognition for Indoor Fall Detection in 360-Degree Videos Using Deep Learning Techniques

Indirect Recognition of Predefined Human Activities

“…Wiljer et al [ 4 ] suggested improving health care by developing an artificial intelligence-enabled healthcare practice. Many of the works in the field of activity recognition are emphasizing fall detections [ 5 , 6 , 7 ]. Sadreazami et al [ 5 ] proposed using the Standoff Radar and a time series-based method for detecting fall incidents in human daily activities.…”

“…Ahamed et al [ 6 ] investigated accelerometer-based fall detection, the Feed Forward Neural Network and Long Short-Term Memory based on deep learning networks, applied to detect falls. Dhiraj et al [ 7 ] proposed two vision-based solutions, one using convolutional neural networks in 3D-mode and another using a hybrid approach by combining convolutional neural networks and long short-term memory networks using 360-degree videos for human fall detection.…”