Under the background of global aging and empty nest family, the tumble of seniors has attracted a great deal of attention. To provide help for seniors and relieve the injury of tumble, a tumble recognition algorithm based on image processing and multi-features fusion is proposed. In view of the prospect of extraction, we propose an algorithm that combines three-frame difference method and background subtraction division of target by weight, then extract the height, ratio of width to height, the center of mass, the perimeter of a rectangle, Hu moments′ and Zernike moments of target contour, using five experimenters′ walking, siting down, squating down and tumbling as the experimental samples. The algorithm realizes tumble detection and recognition by training and predicting support vector machine (SVM) after parameter optimization. The experimental results show that the proposed algorithm is efficient and fast with easy implementation. The average recognition rate is more than 95%.