Amsterdam-AI-Team/Tree_Detection_in_Aerial_Point_Clouds

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European Union Pu...
Created over 2 years ago
Updated over 1 year ago

Amsterdam-AI-Team/Tree_Detection_in_Aerial_Point_Clouds

Amsterdam-AI-Team

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Data processing for urban tree detection in aerial 3D point clouds. Analyzing tree data in Amsterdam 🌳

Urban_PointCloud_Processing

Repository for automatic classification and labeling of Urban PointClouds using data fusion and region growing techniques.

3D_Ground_Segmentation

A ground segmentation algorithm for 3D point clouds based on the work described in “Fast segmentation of 3D point clouds: a paradigm on LIDAR data for Autonomous Vehicle Applications”, D. Zermas, I. Izzat and N. Papanikolopoulos, 2017. Distinguish between road and non-road points. Road surface extraction. Plane fit ground filter

1.5-meter-monitor

Because of COVID19 measures have been taken to prevent person to person detection, one of the most influential and important new regulation is to keep 1.5 meters distance from each other. To help remind citizens to maintain this distance we have created the 1.5 meter monitor.

Geolocalization_of_Street_Objects

In this repository, an approach is implemented to automatically detect and geolocate public objects, solely based on public available panoramic images. The objects of interest are assumed to be stationary, compact and observable from several locations each. In this project the objects being detected are bicycle symbols.

Urban_PointCloud_Sidewalk_Width

Measuring sidewalk widths for Amsterdam using Urban Point Clouds and cadastral data.

Houseboat_Detection_in_Satellite_Images

Detect, segment and geolocate houseboats in Amsterdam using satellite images.

Jupyter Notebook

Urban_PointCloud_Analysis

This repository contains methods for the automatic extraction of urban street furniture from labeled PointClouds.