Onboard Video Stabilization for Unmanned Air Vehicles

Cross, Nicholas Stewart

doi:10.15368/theses.2011.67

Cited by 2 publications

(2 citation statements)

References 17 publications

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“…The center of this field of regard is the look direction and the ray 2 originating at the sensor and extending through the center field of regard off into infinity defines the payload's line of sight, abbreviated LOS. For this work it is assumed that any curvature of this line of sight between the payload and its 1 Field of Regard is associated with generic directional payloads, both transmitting and sensing type payloads. The term Field of View, FOV, is a field of regard more specifically associated with sensing type payloads.…”

Section: Line Of Sight Stabilizationmentioning

confidence: 99%

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Control System Development for small UAV Gimbal

Brake¹

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Section: Line Of Sight Stabilizationmentioning

confidence: 99%

“…The video processing algorithms implemented on the Tigereye are describes in [1]. The electronic target tracking algorithm identifies features inside the white rectangle and transmits their pixel X,Y location to the mechanical stabilization board.…”

Section: Target Trackingmentioning

confidence: 99%

Control System Development for small UAV Gimbal

Brake¹

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Instantaneous video stabilization for unmanned aerial vehicles

Yang

et al. 2014

J. Electron. Imag.

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Video stabilization is a critical step for improving the quality of videos captured by unmanned aerial vehicles. However, the complicated scenarios in the video and the need for instantaneously presenting a stabilized image posed significant challenges to the existing methods. In this work, an instantaneous video stabilization method for unmanned aerial vehicles is proposed. This new approach serves several purposes: smoothing the video motion in both two-dimensional and three-dimensional (3-D) scenes, decreasing the lags in response, and instantaneously providing the stabilized image to users. For each input frame, our approach regenerates four short motion trajectories by applying interframe transformations to the four corners of the image rectangle. An adaptive filter is then performed to smooth motion trajectories and suppress the lags in response simultaneously. Finally, at the stage of image composition, the quality of image is considered for selecting a visually plausible stabilized video. Experiments show that our approach can stabilize various videos without the need for user interaction or costly 3-D reconstruction, and it works as an instant-process for videos from an online source.

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Onboard Video Stabilization for Unmanned Air Vehicles

Cited by 2 publications

References 17 publications

Control System Development for small UAV Gimbal

Control System Development for small UAV Gimbal

Instantaneous video stabilization for unmanned aerial vehicles

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