This repository is related with the next paper. Please cite us if this code is useful to you. Barral, V., Dominguez-Bolano, T., Escudero, C. J., & Garcia-Naya, J. A. An IoT System for Smart Building Combining Multiple mmWave FMCW Radars Applied to People Counting. Python Scripts count_plot.py: Generates a plot comparing image tracking estimation, radar with DBSCAN, and radar with OPTICS. Use example: python count_plot.py count_video_full.log count_radar_moving_average_30_optics.log count_radar_moving_average_30_dbscan.log "Video" "Radar with OPTICS" "Radar with DBSCAN" average_count_full_optics_dbscan.pdf Radar measurements test_0.bag: FMCW mmWave radar measurements from three IWR6843 devices (ISK and AOP). Is a ROS (Robotic Operative System) log, can be played with rosbag play test_0.bag Radar people counting logs count_radar_moving_average_30_dbscan.log: radar people counting estimation using a 30 seconds moving average and DBSCAN as clustering algorithm. count_radar_moving_average_30_optics.log: radar people counting estimation using a 30 seconds moving average and OPTICS as clustering algorithm. Image tracking Videos test_0_cam_0.mp4: Camera 0 capture. test_0_cam_1.mp4: Camera 1 capture. Image tracking logs test_0_cam_0_interp.txt: People count in camera 0 test_0_cam_1_interp.txt: People count in camera 1 The files have the following format: frame_number, track_id, bb_left, bb_top, bb_width, bb_height, conf, x, y, z The coordinates x, y, z are always -1 The bb fields define the bounding box of the detection If multiple people are detected in a frame, there are several lines with that frame_number, but with different track_ids. Image people counting logs count_video_full.log: image tracking people counting estimation using a 30 seconds moving average.