期刊名称：International Journal on Electrical Engineering and Informatics
印刷版ISSN：2085-6830
出版年度：2019
卷号：11
期号：4
页码：697-712
DOI：10.15676/ijeei.2019.11.4.5
出版社：School of Electrical Engineering and Informatics
摘要：Since the Viola and Jones' method on real-time face detection was proposed in 2001,numerous works for object detection, person recognition, and object tracking have beenpublished by papers and journals. Each method has its strong points and drawbacks. That meansthat in a system which only employs a standalone method, we could only get either speed oraccuracy. In this paper, we proposed a state-machine method to combine face recognition, facedetection, and tracker to harness the tracker promptness while maintaining the ability todistinguish the person of interest with the other person and backgrounds, to overcome thelimitations of the standalone method. Subsequently, the information gathered from this imageprocessing side will be delivered to the hardware tracker. The image processing side becomes avisual sensor that provides feedback or measurement value i.e. center point coordinate valuefrom the detected face.The 2 DOF hardware tracker camera platform being used implements Model PredictiveControl to calculate required control action thus the platform is able to track the target object,keeping it at the center of the frame. MPC method is chosen because it produces an optimalcontrol signal while considering the input signal saturation aspect. The MPC control signalsdeliver a good control pan and tilt system response with rise time < 1 second and overshoot<15%. It is also noticed that the FSM implemented in this paper is able to meet the goal with aconsiderable performance for indoor settings.
关键词：computer vision; person recognition; state machine; tracker; visual servoing; MPC;pan;tilt camera
