Multispectral pedestrian detection is becoming increasingly important in the field of computer vision due to its applications in driver assistance, surveillance, and monitoring. In this paper, we propose a brightness aware model for pedestrian detection using deep learning. A novel brightness aware mechanism depicts various illumination conditions, so as to enable prediction of day/ night scenario. Based on the detection of the brightness aware mechanism, a color or thermal model is used to detect pedestrians under day or night conditions respectively. The proposed method trained on FLIR-ADAS Thermal dataset and PASCAL VOC Color dataset, has achieved a mAP of '81.27%', which outperforms the current state of the art.
cited By 0; Conference of 8th IEEE International Conference on Communication and Signal Processing, ICCSP 2019 ; Conference Date: 4 April 2019 Through 6 April 2019; Conference Code:147623
K. N. R. Chebrolu and Dr. (Col.) Kumar P. N., “Deep Learning based Pedestrian Detection at all Light Conditions”, in Proceedings of the 2019 IEEE International Conference on Communication and Signal Processing, ICCSP 2019, 2019, pp. 838-842.