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Descrizione
KITTI Dataset
Overview
Excerpts from the following papers:
- Vision meets Robotics: The KITTI Dataset, 2013
- Are we ready for Autonomous Driving?The KITTI Vision Benchmark Suite, 2012
Data Description
-
Image:
image_2- 8-bit
PNGfile:training/image_2/000085.png

- 8-bit
-
Velodyne:
velodyne- Each point stored as floating point binaries:
[x, y, z, reflectance] - Number of points per scan is not constant
- Each point stored as floating point binaries:
-
Calibration:
calib- Variables
P0:P1:P2:P3:R0_rect:Tr_velo_to_cam:Tr_imu_to_velo:
- To project a point from Velodyne coordinates into the color image, you can use this formula
x = P2 * R0_rect * Tr_velo_to_cam * y(for the left color image)x = P3 * R0_rect * Tr_velo_to_cam * y(for the right color image)
- Variables
-
Label:
label_2- For each dynamic object within the reference camera’s field of view, we provide annotations in the form of 3D bounding box tracklets.

Values Name Description 1 type Describes the type of object: 'Car', 'Van', 'Truck', 'Pedestrian', 'Person_sitting', 'Cyclist', 'Tram', 'Misc' or 'DontCare' 1 truncated Float from 0 (non-truncated) to 1 (truncated), where truncated refers to the object leaving image boundaries 1 occluded Integer (0,1,2,3) indicating occlusion state: 0 = fully visible, 1 = partly occluded, 2 = largely occluded, 3 = unknown 1 alpha Observation angle of object, ranging [-pi..pi] 4 bbox 2D bounding box of object in the image (0-based index): contains left, top, right, bottom pixel coordinates 3 dimensions 3D object dimensions: height, width, length (in meters) 3 location 3D object location x,y,z in camera coordinates (in meters) 1 rotation_y Rotation ry around Y-axis in camera coordinates [-pi..pi] 1 score Only for results: Float, indicating confidence in detection, needed for p/r curves, higher is better. training/label_2/000085.txt
Van 0.90 0 -0.79 0.00 57.67 245.43 374.00 2.46 2.03 5.35 -5.26 1.68 5.45 -1.53 Cyclist 0.00 0 -1.54 678.16 164.16 705.93 243.78 1.82 0.59 1.89 1.96 1.63 17.42 -1.43 Pedestrian 0.00 0 0.90 304.95 177.99 359.91 304.07 1.57 0.52 0.62 -3.69 1.64 9.37 0.54 Car 0.27 3 -2.42 0.00 179.86 156.79 244.69 1.44 1.62 3.91 -13.19 1.62 17.05 -3.07 DontCare -1 -1 -10 644.98 164.60 670.02 188.60 -1 -1 -1 -1000 -1000 -1000 -10 DontCare -1 -1 -10 739.77 173.98 799.19 209.44 -1 -1 -1 -1000 -1000 -1000 -10 - For each dynamic object within the reference camera’s field of view, we provide annotations in the form of 3D bounding box tracklets.