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Image Processing

Visual Registration and Mosaic for Unmanned Aerial Vehicle

Unmanned Aerial Vehicles (UAVs) always execute the tasks in the Unknown Envrionments, such as Inside of Building and Outside of (High) Terrains, however, the whole informations, such as Obstacles and Special Targets in different direction and distance(depth of image), about these unknown envrionments can help UAVs to carry out the tasks autonomously better or operators to make a better decision for the whole task, and the Field of View (FOV) for camera also always small, it means that UAV often just show the local environment using just one camera, however, the Registration and Mosaic algorithms can solve this limitation in order to obtain a much larger FOV.

    Unmanned Aerial Vehicles (UAVs) always execute the tasks in the Unknown Envrionments, such as Inside of Building and Outside of (High) Terrains, however, the whole informations, such as Obstacles and Special Targets in different direction and distance(depth of image), about these unknown envrionments can help UAVs to carry out the tasks autonomously better or operators to make a better decision for the whole task, and the Field of View (FOV) for camera also always small, it means that UAV often just show the local environment using just one camera, however, the Registration and Mosaic algorithms can solve this limitation in order to obtain a much larger FOV.

Vision-based pose estimation using 3D markers

Sometimes, UAVs fly in GPS-denied environments, where there is no easy way for them to determine their own pose, relative to their surroundings. This research line tries to address this problem using visual information from an onboard camera.

Optical flow (sparse L-K) and features based matching methods

Optical Flow and features based matching methods are used on different methods like visual tracking and servoing, homography calculation, video stabilization and mosaics building among others.