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TME Motorway Dataset
2D Box
2D Classification
许可协议: Unknown

Overview

The “Toyota Motor Europe (TME) Motorway Dataset” is composed by 28 clips for a total of approximately 27 minutes (30000+ frames) with vehicle annotation. Annotation was semi-automatically generated using laser-scanner data. Image sequences were selected from acquisition made in North Italian motorways in December 2011. This selection includes variable traffic situations, number of lanes, road curvature, and lighting, covering most of the conditions present in the complete acquisition.

The dataset comprises:

  • Image acquisition: stereo, 20 Hz frequency , 1024x768 grayscale losslessly compressed images, 32° horizontal field of view, bayer coded color information (in OpenCV use CV_BayerGB2GRAY and CV_BayerGB2BGR color conversion codes; please note that left camera was rotated upside down, convert to color/grayscale BEFORE flipping the image). A checkboard calibration sequence is made available.
  • Laser-scanner generated vehicle annotation and classification (car/truck).
  • A software evaluation toolkit (C++ source code).

The data provided is timestamped, and includes extrinsic calibration.
The dataset has been divided in two sub-sets depending on lighting condition, named “daylight” (although with objects casting shadows on the road) and “sunset” (facing the sun or at dusk). For each clip, 5 seconds of preceding acquisition are provided, to allow the algorithm stabilizing before starting the actual performance measurement.

The data has been acquired in cooperation with VisLab (University of Parma, Italy), using the BRAiVE test vehicle.

数据概要
数据格式
image,
数据量
30K
文件大小
--
| 数据量 30K | 大小 --
TME Motorway Dataset
2D Box 2D Classification
许可协议: Unknown

Overview

The “Toyota Motor Europe (TME) Motorway Dataset” is composed by 28 clips for a total of approximately 27 minutes (30000+ frames) with vehicle annotation. Annotation was semi-automatically generated using laser-scanner data. Image sequences were selected from acquisition made in North Italian motorways in December 2011. This selection includes variable traffic situations, number of lanes, road curvature, and lighting, covering most of the conditions present in the complete acquisition.

The dataset comprises:

  • Image acquisition: stereo, 20 Hz frequency , 1024x768 grayscale losslessly compressed images, 32° horizontal field of view, bayer coded color information (in OpenCV use CV_BayerGB2GRAY and CV_BayerGB2BGR color conversion codes; please note that left camera was rotated upside down, convert to color/grayscale BEFORE flipping the image). A checkboard calibration sequence is made available.
  • Laser-scanner generated vehicle annotation and classification (car/truck).
  • A software evaluation toolkit (C++ source code).

The data provided is timestamped, and includes extrinsic calibration.
The dataset has been divided in two sub-sets depending on lighting condition, named “daylight” (although with objects casting shadows on the road) and “sunset” (facing the sun or at dusk). For each clip, 5 seconds of preceding acquisition are provided, to allow the algorithm stabilizing before starting the actual performance measurement.

The data has been acquired in cooperation with VisLab (University of Parma, Italy), using the BRAiVE test vehicle.

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