Online Human-Assisted Learning using Random Ferns Description: This file contains the code to perform online and human-assisted learning using random ferns . More specifically, this code allows to learn and detect simultaneously one specific object using human assistance. Initially, the human selects via the computer's mouse the object in the image that he/she wants to learn and recognize in future frames. Subsequently, the random ferns classifier is initially computed using a set of training samples. Positive samples are extracted using random shift transformations over the object, whereas negative samples are random patches from the background. In run time, the random ferns detect the object and use their own hypotheses to update and refine the classifier (self-learning). However, in cases where the classifier is uncertain about its output (sample label), the classifier requests the human assistance in order to label the difficult samples. In this case, the program asks to the human user if the object detection (bounding box) is correct or not. The user should answer yes (y) or not (n) via the keyboard. If you make use of this code for research articles, we kindly encourage to cite the references , listed below. This code is only for research and educational purposes. Requirements: 1. opencv (e.g opencv 2.4.9) 2. cmake Compilation: 1. mkdir build 2. cd build 3. cmake .. 3. make 4. ./detector (using webcam) Comments: 1. The program works at any input image resolution. However, the screen information like score, results, etc, are displayed for a resolution of 640x480 pixels. This is the default resolution. If you change the resolution you must sure that the functions: fun_show_frame and fun_update_classifiers are shown properly. We recommend not using a resolution lower of 640x480 pixels. 2. The program parameters are defined in the file parameters.txt located in the files folder. In this file you can change the detector parameters and program funcionalities. Keyboard commands: p: pause the video stream ESC: exit the program space: enable/disable object detection y: yes n: no Contact: Michael Villamizar email@example.com Institut de Robòtica i Informàtica Industrial, CSIC-UPC Barcelona - Spain 2015 References:  Online Human-Assisted Learning using Random Ferns M. Villamizar, A. Garrell, A. Sanfeliu and F. Moreno-Noguer International Conference on Pattern Recognition (ICPR), 2012.  Proactive Behavior of an Autonomous Mobile Robot for Human-Assisted Learning A. Garrell, M. Villamizar, F. Moreno-Noguer and A. Sanfeliu International Symposium on Robot and Human Interactive Communication (IEEE RO-MAN), 2013.