Waymo Open Dataset is a multimodal (camera + LiDAR) dataset covering a wide range of areas in the US (namely San Francisco, Mountain View, Los Angeles, Detroit, Seattle, Phoenix). It is one of the largest publicly available datasets for investigating a wide range of interesting aspects of machine perception and autonomous driving technology, such as … Continue reading Waymo Open Dataset: Open3D Point Cloud Viewer

Particle filters comprise a broad family of Sequential Monte Carlo (SMC) algorithms for approximate inference in partially observable Markov chains. The objective of a particle filter is to estimate the posterior density of the state variables given the observation variables. A generic particle filter estimates the posterior distribution of the hidden states using the observation … Continue reading Particle filters with Python

A Kd-tree, or K-dimensional tree, is a generalization of a binary search tree that stores points in a k-dimensional space. In computer science it is often used for organizing some number of points in a space with k dimensions. Kd-trees are very useful for range and nearest neighbor (NN) searches, it is a very common operation … Continue reading Kd-tree and Nearest neighbor (NN) search (2D case)

RANSAC or "RANdom SAmple Consensus" is an iterative method to estimate parameters of a mathematical model from a set of observed data which contains outliers. It is one of classical techniques in computer vision. My motivation for this post has been triggered by a fact that Python doesn't have a RANSAC implementation so far. The … Continue reading Robust linear model estimation using RANSAC – Python implementation

In this post we will talk about convex hulls which have a broad range of applications in mathematics, computer science and surely image processing / computer vision. In mathematics the convex hull (sometimes also called the convex envelope) of a set of points X in the Euclidean plane or Euclidean space is the smallest convex … Continue reading Convex hull: how to tell whether a point is inside or outside?

Assume you are working on the image /video segmentation problem. Sooner or later a day is  coming when you need to present your (hopefully good) results to other people on a conference, project meeting, in a paper, whatever. Usually segmentation results are represented by a matrix of integers standing for region labels which are supposed … Continue reading Python: putting segments on top of the input image

Here I would like to show you some changes in the source code of the Robust least squares fitting required for a general quadric surface (fitting of the planar model was introduced in the previous post). Assume you want to fit a set of data points in the three-dimensional space with a general quadric described … Continue reading Robust Least Squares for fitting data (quadric surface)