camvid

The Cambridge-driving Labeled Video Database (CamVid) is the first collection of videos with object class semantic labels, complete with metadata. The database provides ground truth labels that associate each pixel with one of 32 semantic classes.<br><br>The database addresses the need for experimental data to quantitatively evaluate emerging algorithms. While most videos are filmed with fixed-position CCTV-style cameras, our data was captured from the perspective of a driving automobile. The driving scenario increases the number and heterogeneity of the observed object<br>classes.<br>剑桥驾驶标注视频数据库（Cambridge-driving Labeled Video Database，简称CamVid）是首个带有目标类别语义标注且附带完整元数据的视频数据集。该数据库提供了将每个像素映射至32个语义类别之一的基准真值标签（ground truth labels）。 本数据集旨在满足通过实验数据对新兴算法进行量化评估的需求。尽管多数视频采用固定机位闭路电视（CCTV）式相机拍摄，但本数据集采用车载拍摄视角。驾驶场景提升了所观测目标类别的数量与异质性。

搜集汇总

背景与挑战

背景概述

CamVid数据集是一个包含32个语义类别像素级标签的驾驶场景视频数据库，旨在为算法评估提供实验数据。其独特之处在于采用驾驶汽车视角，增加了观察对象的多样性和异质性。