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Our vehicle is equipped with six cameras, mounted on the front, back, left, and right, each with a different height. I have tested cameras with similar heights and achieved good results. However, I found that when I use all the cameras, some of them have significantly different heights, resulting in poor performance.
The code below only uses one camera height to estimate flat plane. I would like to know how I should modify the code to adapt to these multiple cameras?Any reply would be appreciated.
@MrlynnBei Hi, you can refer #42 for help. The estimated flat plane is not always good.
Okk. Thanks! And I have another question: Can the world coordinate system of the camera pose be an ENU system? or Can the camera pose be expressed in ENU coordinates?(tf_enu_cami)?
I saw the code that transform the tf_cam0_cami to tf_chassis_cami:(Am I understanding this correctly?)
camera_poses = self.camera2chassis @ camera_poses # refrece to chassis
@MrlynnBei We use local corrdinate systems and save a tranform from local to global coordinate. It would be better for understanding and reconstruction.
Hi, thank you for sharing the great work!
Our vehicle is equipped with six cameras, mounted on the front, back, left, and right, each with a different height. I have tested cameras with similar heights and achieved good results. However, I found that when I use all the cameras, some of them have significantly different heights, resulting in poor performance.
The code below only uses one camera height to estimate flat plane. I would like to know how I should modify the code to adapt to these multiple cameras?Any reply would be appreciated.
` # 6. estimate flat plane
self.file_check()
self.label_valid_check()
ref_camera2world_all = np.array(self.ref_camera2world_all)
transform_normal2origin = robust_estimate_flatplane(np.array(ref_camera2world_all)[:, :3, 3]).astype(np.float32)
transform_normal2origin[0, 3] = -self.choose_pt[0]
transform_normal2origin[1, 3] = -self.choose_pt[1]
transform_normal2origin[2, 3] += self.camera_height
self.ref_camera2world_all = transform_normal2origin[None] @ self.ref_camera2world_all
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