Datasets:

PengYu-Team
/

S3E

	%YAML:1.0

	#--------------------------------------------------------------------------------------------
	# Left Camera Parameters.
	#--------------------------------------------------------------------------------------------
	Camera.type: "PinHole"

	# Camera calibration and distortion parameters (OpenCV)
	Camera.fx: 1172.771733138536
	Camera.fy: 1172.364005984343
	Camera.cx: 617.941545715258
	Camera.cy: 507.672727295385

	Camera.k1: -0.052628389768906
	Camera.k2: 0.100832689624109
	Camera.p1: 0.000395112517197
	Camera.p2: 0.000362060505238

	Camera.width: 1224
	Camera.height: 1024

	# Camera frames per second
	Camera.fps: 10.0

	# stereo baseline times fx (unit: m x pixel)
	Camera.bf: 422.197823929873

	#--------------------------------------------------------------------------------------------
	# IMU noise
	#--------------------------------------------------------------------------------------------
	IMU.NoiseGyro: 1.0451440924866223e-02
	IMU.NoiseAcc: 1.0919628856399554e-02
	IMU.GyroWalk: 8.1770009351257180e-05
	IMU.AccWalk: 2.1851827629113259e-04
	IMU.Frequency: 100

	# Transformation from left camera to imu
	Tic: !!opencv-matrix
	rows: 4
	cols: 4
	dt: d
	data: [ 0.00671209, -0.00971447, 0.99993029, 0.14118513,
	-0.99993865, -0.00887635, 0.00662591, 0.1552482,
	0.00881136, -0.99991342, -0.00977345, 0.01917531,
	0.0, 0.0, 0.0, 1.0]

	#--------------------------------------------------------------------------------------------
	# Stereo Rectification. Only if you need to pre-rectify the images.
	#--------------------------------------------------------------------------------------------
	LEFT.height: 1024
	LEFT.width: 1224
	LEFT.D: !!opencv-matrix
	rows: 1
	cols: 5
	dt: d
	data: [-0.052628389768906, 0.100832689624109, 0.000395112517197, 0.000362060505238, 0.0]
	LEFT.K: !!opencv-matrix
	rows: 3
	cols: 3
	dt: d
	data: [1172.771733138536, 0.0, 617.941545715258,
	0.0, 1172.364005984343, 507.672727295385,
	0.0, 0.0, 1.0]
	LEFT.R: !!opencv-matrix
	rows: 3
	cols: 3
	dt: d
	data: [1.0, 0.0, 0.0,
	0.0, 1.0, 0.0,
	0.0, 0.0, 1.0]
	LEFT.Rf: !!opencv-matrix
	rows: 3
	cols: 3
	dt: d
	data: [1.0, 0.0, 0.0,
	0.0, 1.0, 0.0,
	0.0, 0.0, 1.0]
	LEFT.P: !!opencv-matrix
	rows: 3
	cols: 4
	dt: d
	data: [1172.771733138536, 0.0, 617.941545715258, 0.0,
	0.0, 1172.364005984343, 507.672727295385, 0.0,
	0.0, 0.0, 1.0, 0.0]

	RIGHT.height: 1024
	RIGHT.width: 1224
	RIGHT.D: !!opencv-matrix
	rows: 1
	cols: 5
	dt: d
	data: [-0.052817970234810, 0.100073648217903, 0.000987319404990, 0.000078198322045, 0.0]
	RIGHT.K: !!opencv-matrix
	rows: 3
	cols: 3
	dt: d
	data: [1172.549603999100, 0.0, 617.477465353483,
	0.0, 1173.241586185178, 516.335518983269,
	0.0, 0.0, 1.0]
	RIGHT.R: !!opencv-matrix
	rows: 3
	cols: 3
	dt: d
	data: [0.999994846143267, 0.003159631643868, -0.000569574209205,
	-0.003162491376236, 0.999982035625659, -0.005091863534975,
	0.000553475564009, 0.005093638565765, 0.999986874169337]
	RIGHT.P: !!opencv-matrix
	rows: 3
	cols: 4
	dt: d
	data: [1172.549603999100, 0.0, 617.477465353483, -361.1747016345565 ,
	0.0, 1173.241586185178, 516.335518983269, -5.2678945955122,
	0.0, 0.0, 1.0, -1.5931129591554]

	#--------------------------------------------------------------------------------------------
	# Transformation from left camera to lidar
	#--------------------------------------------------------------------------------------------
	Tlc: !!opencv-matrix
	rows: 4
	cols: 4
	dt: d
	data: [0.016401767702498, -0.010112948899873, 0.999814337905184, 0.128861294507233,
	-0.999053252579189, -0.040462795913874, 0.015980008065579, 0.196875730840019,
	0.040293678501436, -0.999129866639658, -0.010767035870758, -0.126632260291528,
	0.0, 0.0, 0.0, 1.000000000000000]