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Daimler Mono Pedestrian Classification Benchmark
创建来自Hello Dataset / Robert
概要
活动

Overview

The dataset consists of two parts:

  • a base data set. The base data set contains a total of 4000 pedestrian- and 5000 non-pedestrian samples cut out from video images and scaled to common size of 18x36 pixels.
  • additional non-pedestrian images. An additional collection of 1200 video images NOT containing any pedestrians, intended for the extraction of additional negative training examples.

Data Collection

Pedestrian images were obtained from manually labeling and extracting the rectangular positions of pedestrians in video images. Video images were recorded at various (day) times and locations with no particular constraints on pedestrian pose or clothing, except that pedestrians are standing in upright position and are fully visible. As non-pedestrian images, patterns representative for typical preprocessing steps within a pedestrian classification application, from video images known not to contain any pedestrians. We chose to use a shape-based pedestrian detector that matches a given set of pedestrian shape templates to distance transformed edge images (i.e. comparatively relaxed matching threshold).

License

Custom

数据集信息
应用场景PersonAutonomous Driving
标注类型Classification
LicenseCustom
更新时间2021-03-24 22:53:28
数据概要
数据格式Image
数据数量0
文件大小399KB
标注数量0
版权归属方
Daimler AG
标注方
未知
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