Perceiving human actions is viewed as exceptionally fundamental in interpersonal interaction and interpersonal relationships because of its inclination of giving data in regards to a group’s nature, including members’ personalities and psychological health. The comparison is conducted on any kind of remark against a predetermined pattern in machine vision, and the activity is recognized and labelled later on. The SVM is the classifier which is applied in the previously for recognizing the activities of individuals. The SVM classifier performs poorly at identifying human activities, necessitating the development of innovative models. The study described here proposes a hybrid technique in which a Convolutional Neural Network is combined with a Long Short-Term Memory Network Model. The proposed approach achieves accuracy of up to 98% for the human activity recognition.