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KITTI-tracking
创建来自Data Decorators / AChenQ
概要
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Overview

The object tracking benchmark consists of 21 training sequences and 29 test sequences. Despite the fact that we have labeled 8 different classes, only the classes 'Car' and 'Pedestrian' are evaluated in our benchmark, as only for those classes enough instances for a comprehensive evaluation have been labeled.

Data Collection

Our recording platform is a Volkswagen Passat B6, which has been modified with actuators for the pedals (acceleration and brake) and the steering wheel. The data is recorded using an eight core i7 computer equipped with a RAID system, running Ubuntu Linux and a real-time database. We use the following sensors:

The laser scanner spins at 10 frames per second, capturing approximately 100k points per cycle. The vertical resolution of the laser scanner is 64. The cameras are mounted approximately level with the ground plane. The camera images are cropped to a size of 1382 x 512 pixels using libdc's format 7 mode. After rectification, the images get slightly smaller. The cameras are triggered at 10 frames per second by the laser scanner (when facing forward) with shutter time adjusted dynamically (maximum shutter time: 2 ms). Our sensor setup with respect to the vehicle is illustrated in the following figure. Note that more information on calibration parameters is given in the calibration files and the development kit (see raw data section).

img img

Citation

Please use the following citation when referencing the dataset:

@INPROCEEDINGS{[Geiger2012CVPR](http://www.cvlibs.net/publications/Geiger2012CVPR.pdf),
 author = {[Andreas Geiger](http://www.cvlibs.net/) and [Philip Lenz](http://www.mrt.kit.edu/mitarbeiter_lenz.php)
and [Raquel Urtasun](http://ttic.uchicago.edu/~rurtasun)},
 title = {Are we ready for Autonomous Driving? The KITTI Vision Benchmark Suite},
 booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)},
 year = {2012}
}

License

CC BY-NC-SA 3.0

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数据集信息
应用场景Autonomous Driving
标注类型Box2DBox2D TrackingBox3DBox3D Tracking
LicenseCC BY-NC-SA 3.0
更新时间2021-03-24 23:37:47
数据概要
数据格式Point CloudImage
数据数量38.2k
文件大小35GB
标注数量94508
版权归属方
Max Planck Institute for Intellgent Systems
标注方
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