Fall Detection with CNN architecture

Fall detection is a major problem in healthcare. Old people fall often and there should be immediate aid for them as injury can be serious, even lead to death. In this project, we will use Convolutional Neural Network architecture to detect whether a person has fallen or not in a given image. For this purpose, we use public dataset that contains videos of falling people. Each frame has been given as a picture, and we use 2 videos that make a total of 240 images.