Falls have become common nowadays among the elderly. It has been noted by the World Health Organization (WHO) that approximately one out of 3 elderly people aged above 65 living alone tend to fall and the rate can increase in the coming years. Many ideas have been proposed and worked out including using of inertial sensors, accelerometer and gyro meter. This paper proposes a method where the video from the camera is processed and the features are extracted. The features are extracted using HOG and statistical approach. The database contains fall and daily activities and Support Vector Machine (SVM) is used for classification which gives an accuracy of 100%.
Image Processing, Machine Learning, HOG, Statistical feature, SVM
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