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2: Illustration of camera mounting positions on the test vehicle, a standard station wagon. The reference camera is mounted in front. The left and right facing cameras (C 2 and C 4 ) are mounted close to the side mirrors. The distance between these cameras is approximately 1.8m and the distance between the front and rear-mounted camera is approximately 4.78m. The specified heights, h 1 to h 4 , were determined during the (offline) reference calibration.
Source publication
Multi-camera systems are being deployed in a variety of vehicles and mobile robots today. Applications of such systems range from driver assistance functions such as rendering a virtual panoramic view to surround sensing, which is a prerequisite for partially and fully automated driving. In order to derive metric quantities such as angles and dista...
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Citations
... The parallax caused by the misalignment of NPPs is larger for object panoramas than background panoramas. Depending on the camera configuration, the parallax level become severe [19]. For successful image stitching it is necessary to correctly align the overlapping areas of the input images. ...
... Residual misalignment error (planar parallax) of the object panorama was quantitatively evaluated using a panorama assessment method [17,19]. Table 1 shows the residual misalignment error of the object panorama resulted from the existing method and the proposed method. ...
Conventional panorama techniques create a wide-angle image by stitching images taken from the same viewpoint. In contrast, the method proposed in this work produces an unwrapped surface image of a three-dimensional spherical object. Traditionally, in order to construct a panoramic image including multiple faces of an object, consecutive video frames must be captured around the object so that images with small parallax can be stitched together to avoid ghost artifacts. In this study, however, we use only two input images taken from different viewpoints to construct the panoramic surface image of a spherical object. This kind of constraint can occur when the cameras have limitation on changing their poses. The acquired two input images have a larger parallax than the video frames. Therefore, in order to align the overlapping regions of the large-parallax images, an image-morphing method with a curved interpolation line is proposed. The interpolation curve is designed for a spherical target object and it reduces dent distortion. As image morphing is highly vulnerable to feature mismatches, the corresponding features in the parallax images are paired by active feature matching using a structured light. During image composition, the seam boundary that minimizes ghost effects at the transition between images is determined based on image similarity. The experimental results for large-parallax images with an angle difference of 60° demonstrate the effectiveness of the proposed method.
