abhi1kumar
commented
10 months ago it is the product of the Intrinsic and Extrinsic parameters of the camera, where the Extrinsic parameters are the rotation matrix and translational vector.
You are correct.
Here's a simple matrix I got using checkerboard correction in matlab. He seems to have problems at [0,3] and [1,3]. I use this matrix to replace P2 in calib，but the inference results in null. It seems worse than before when you suggested that I just use something like containing only the Intrinsic parameters without the Extrinsic parameters.
Calibration matrix is known apriori in monocular 3D detection task. Depending on the calibration matrix, the predicted 3D boxes differ in 3D space.
It is possible to get inference results using only the Intrinsic parameters， except that the 3D box do not match.
I assume this is a question. Using only intrinsics without camera extrinsics is a bad idea unless the extrinsics is a 4x4 identity matrix. (Rotation is identity matrix and translation is zero vector)
P matrix in calib in KITTI, what exactly does it mean? According to my search, it is the product of the Intrinsic and Extrinsic parameters of the camera, where the Extrinsic parameters are the rotation matrix and translational vector. Here's a simple matrix I got using checkerboard correction in matlab. He seems to have problems at [0,3] and [1,3]. I use this matrix to replace P2 in calib，but the inference results in null. It seems worse than before when you suggested that I just use something like containing only the Intrinsic parameters without the Extrinsic parameters. It is possible to get inference results using only the Intrinsic parameters， except that the 3D box do not match exactly I'm sorry to bother you again, but this question has been bothering me for a long time and I can't find any useful information!