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High-accuracy Outdoor RGB-D Video Sequence for Semantic Scene Parsing
发布日期:2017-07-04 02:37浏览量:1611次

Dataset Overview

The ZPark_2K Dataset contains images, depth maps and pixel level semantic labels of 2 kilometer urban street scenes. 
The figure below shows one image set, including the orginal image, the overlayed segmented image, the depth map, and the color-coded semantic label map. 

The raw data is aquired with a survey grade mobile scanner, together with high-resolution color cameras. The 3D point cloud has an average point density of 2cm and a depth accuracy of better than 1cm. The point cloud is precisely registered with color images. For each image, a synthesized depth map is rendered using the 3D point cloud. In this way, we created an outdoor high-precision RGB-D image sequence with per-pixel semantic labels.

In the following, we give an overview of design choices and detailed data specifications.

Features

  • multiple scan: contains 10 scans of the same street scenes to provide illumination variation
  • semi-auto labeling: 3002 samples with semi-auto pixel level labeling

Class Definitions

class class_id category category_id color_code
others 0 others 0 000000
sky 17 sky 1 87ceeb
motor vehicle 33 moving object 2 400080
non-motor vehicle 34 moving object 2 4080c0
pedestrian 35 moving object 2 404000
rider 36 moving object 2 0080c0
other flat 48 flat 3 804080
motorway 49 flat 3 8000c0
bicycle lane 50 flat 3 c00040
sidewalk 51 flat 3 8080c0
other boundary 64 boundary 4 804040
curb 65 boundary 4 c080c0
other roadblock 80 roadblock 5 c08040
traffic cone 81 roadblock 5 000040
road pile 82 roadblock 5 0000c0
fence 83 roadblock 5 404080
other object 96 object 6 c04080
street lamp 97 object 6 c08080
traffic light 98 object 6 004040
pole 99 object 6 c0c080
traffic sign 100 object 6 4000c0
billboard 101 object 6 c000c0
bus stop board 102 object