Tracking People and Objects with an Autonomous Unmanned Aerial Vehicle using Face and Color Detection

We propose a people and object tracking algorithm for an autonomous unmanned aerial vehicle (UAV). It uses as a surveillance camera and can move anywhere. The camera from UAV is not fixed l ocation a s c losed-circuit t elevision. T he face detection and objection detection are applied to support our proposed. In this research, the UAV model for this paper was AR-Drone 2.0. It has a constraint on the front camera because it has fixed the position of view and cannot change the view during flight. W e d esigned t wo e xperiments. F irst, t he f ace detection using images and applied to the popularity of the face detection, is a Haar-cascade classifier and max-margin object detection with convolutional neural network based features because they have high precision in analysis. Second, color detection system, which only focuses on the color of objects which can developed as an obstacle detection system. The results of the experiment can be accepted to adapt to tracking people and objects in the smart-city.