Trajectory extraction for automatic face sketching
Abstract: This project consists of a series of algorithms employed to obtain a simplistic but realistic representation of a human face. The final goal is for the sketch to be drawn onto paper by a robotic arm with a gripper holding a drawing instrument. The end application is mostly geared towards entertainment and combines the fields of human-machine interaction, machine learning and image processing. The first part focuses on manipulating an input digital image in order to obtain trajectories of a suitable format for the robot to process. Different techniques are presented, tested and compared, such as edge extraction, landmark detection, spline generation and principal component analysis. Results showed that an edge detector yields too many lines, while the generative spline method leads to overly simplistic faces. The best facial depiction was obtained by combining landmark localization with edge detection. The trajectories outputted by the different techniques are passed to the arm through the high level interface provided by ROS, the Robot Operating System and then drawn on paper.
AT THIS PAGE YOU CAN DOWNLOAD THE WHOLE ESSAY. (follow the link to the next page)