In order to improve the recognition accuracy and operation speed of the traditional fall detection system and reduce the false alarm rate and the missing alarm rate， a real-time fall detection algorithm based on fuzzy C-means （FCM） clustering algorithm and convolutional neural network algorithm is proposed. The algorithm takes the depth vision sensor as the data acquisition source， extracts the velocity， the height， the acceleration， and the angle of the cluster center point as the fall recognition feature vector， and uses the combination of threshold analysis and machine algorithm to realize human fall recognition. The experimental results show that the recognition accuracy of the algorithm reaches 99% and the operation speed is 0.178 s， which is higher than those of the traditional algorithm.