Daimler Pedestrian Segmentation Benchmark

by F. Flohr,D. M. GavrilaUnknown

Daimler Pedestrian Segmentation Benchmark

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 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.

Dataset Attributes

Label SVG
TasksSegmentation
Label SVG
CategoriesHumans, Pedestrians
Label SVG
SensorStereovision Camera

Class Labels

pedestrians