On Generating Vehicle Surrounding Images Based on Depth-Adaptive 3D Model
Date Issued
2014
Date
2014
Author(s)
Yeh, Yen-Ting
Abstract
Driving assistance systems help drivers to avoid car accidents by provid-ing warning signals or visual cues of surrounding situations. Instead of the fixed bird’s-eye view monitoring proposed in many previous works, we de-veloped a real-time vehicle surrounding monitoring system, ”Angel Eye”, that can assist drivers to perceive the vehicle surrounding situations more easily. In our system, four fisheye cameras are mounted around a vehicle. To inte-grate these four fisheye camera views, we firstly use fisheye camera calibra-tion method to dewarp the captured images into perspective projection ones. Then, we calculated the camera intrinsic parameters and homography trans-form matrix to get the camera extrinsic parameters. To stitch these dewarpped images, we projected undistorted images into a 3D hybrid projection model and finally the images of the selected viewpoint are rendered.
However, the unknown position of foreground obstacles would cause some visual noises, like image distortion of objects or ghost effect. So we add depth camera into previous system to obtain the depth information of foreground obstacles. The proposed 3D model can be adjusted based on the distance between vehicle and foreground obstacles. The depth-adaptive model can fa-cilitate the rendering of vehicle surroundings in a more realistic and correct way.
Subjects
車輛環周監視系統
視像內插
影像縫合
混合式投影模型
車輛安全空間計算
深度可調三維模型
Type
thesis
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