Pedestrian detection based on faster R-CNN in nighttime by fusing deep convolutional features of successive images

Using Korea advanced institute of science and technology (KAIST) open database, we conducted experiments and observed that the proposed method performed better than the baseline methods at all times (day and night). In addition, through the experiments with national ICT Australia Ltd. (NICTA) open database, we confirm that the proposed method is effective for pedestrian detection at all times. Finally, we present theoretical grounds for the proposed fusion.