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This manuscript describes a UAV implemented with vision and laser based localization algorithm to track and land on a moving platform. Specifically, a pre-designed marker is installed on the moving platform and a downward facing monocular camera is mounted on the UAV for pose estimation. For a robust and precise UAV height estimation, a LiDAR scanning range finder is utilized to determine accurate...
This paper presents a novel solution for a typical small-scaled quad-rotor UAV to autonomously search for and land on a pre-designed marker placed on a rooftop and to observe a digit panel on the opposite building. The UAV is equipped with a downward-facing monocular camera for landing target detection and pose estimation, as well as a front-facing camera for digit panel observation and surveillance...
In this paper, we present an monocular vision-based autonomous navigation system for a commercial quadcoptor. The quadcoptor communicates with a ground-based laptop via wireless connection. The video stream of the front camera on the drone and the navigation data measured on-board are sent to the ground station and then processed by a vision-based SLAM system. In order to handle motion blur and frame...
Motivated by the 2013 International UAV Innovation Grand Prix (UAVGP), we design and implement a real-time vision system for an unmanned helicopter to transfer cargoes between two moving platforms fully autonomously. The key algorithms in the vision system include ellipse detection, ellipse tracking and single-circle-based pose estimation. Comprehensive experiments have verified the efficiency, accuracy...
Determining the motion of an unmanned aerial vehicle in GPS-denied environments is a challenging work. In this paper, we present a systematic design and implementation of a vision aided motion estimation approach for an unmanned helicopter in such a condition. A hierarchical vision scheme is proposed to detect a structured landmark, and find the correspondence between the 3D reference points and the...
In this paper, we provide a unified framework for identifying the source digital camera from its images and for revealing digitally altered images using photo-response nonuniformity noise (PRNU), which is a unique stochastic fingerprint of imaging sensors. The PRNU is obtained using a maximum-likelihood estimator derived from a simplified model of the sensor output. Both digital forensics tasks are...
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