graviti
产品服务
解决方案
知识库
公开数据集
关于我们
avatar
Daimler Pedestrian Segmentation Benchmark
2D Box
2D Polygon
许可协议: Unknown

Overview

Our dataset consist of manually contour-labeled pedestrian images captured from a vehicle-mounted calibrated stereo camera rig in an urban environment. For each pedestrian cutout we provide a 24 bit PNG image, a float disparity map and a ground truth shape.

Dense stereo is computed using the semi-global matching algorithm (H. Hirschmueller, Stereo processing by semi-global matching and mutual information, IEEE Trans. on PAMI, 30(2):328-341, 2008).

The 785 image cut-outs have a height between 34 and 468 pixels and a width between 11 and 267 pixels. In our BMVC’13 publication only samples with a height greater than 120 pixels are used. We provide the samples with an additional 10 % border to each side.

数据概要
数据格式
image,
数据量
785
文件大小
--
| 数据量 785 | 大小 --
Daimler Pedestrian Segmentation Benchmark
2D Box 2D Polygon
许可协议: Unknown

Overview

Our dataset consist of manually contour-labeled pedestrian images captured from a vehicle-mounted calibrated stereo camera rig in an urban environment. For each pedestrian cutout we provide a 24 bit PNG image, a float disparity map and a ground truth shape.

Dense stereo is computed using the semi-global matching algorithm (H. Hirschmueller, Stereo processing by semi-global matching and mutual information, IEEE Trans. on PAMI, 30(2):328-341, 2008).

The 785 image cut-outs have a height between 34 and 468 pixels and a width between 11 and 267 pixels. In our BMVC’13 publication only samples with a height greater than 120 pixels are used. We provide the samples with an additional 10 % border to each side.

0
立即开始构建AI
graviti
wechat-QR
长按保存识别二维码,关注Graviti公众号

Copyright@Graviti
沪ICP备19019574号
沪公网安备 31011002004865号