Fig. 4: Recognition of falling behaviors based on Alpho-RC system.
From: A bioinspired in-materia analog photoelectronic reservoir computing for human action processing
a The computational architecture schematic diagram of Alpho-RC system for human action recognition and prediction. b Examples of five actions including two normal actions (squat and stretch) and three falling actions (fall down, fall to the left and fall to the right) recorded by a mobile phone camera. c Examples of action skeleton frames corresponding to five actions. d Device conductance from 200−1300 µS mapped from the numerical weight values. e The write error tolerance of ±1% during mapping program. f Recognition accuracy of 96.67% obtained by memristor-based output layer. g Comparison of energy consumption per action among Alpho-RC system and algorithms based on various advanced processors.
