features from the input videos is proposed. The model combines the use of 2DCNN and
Stacked LSTM to extract frame-level features through an anisotropic Gunnar Farneback
Optical Flow algorithm. The system is evaluated on the benchmarked datasets namely
UCSD Ped1 and UCSD Ped2, and it achieves an AUC of 95% and 94% respectively. The
experimental results indicate that the proposed method is superior to state-of-the-art …