Implement the Ceres least squares solver from scratch.
Category: least-squares
Haze Removal
I will explain the dehaze algorithm. We will go thought the best paper of CVPR 09 and two related papers which discussed the Soft Matting and Guided Filter.
Facial Landmarks Detection
A tutorial facial landmarks detection. I discussed the AAMs facial landmarks detection and implemented it. With this knowledge, We read a few good papers.
Forward and Inverse Kinematics
A simple introduction to the robot arm problem.
How to Land a Rocket? Part 3, Exploit the Structure
Improve the running time of the rocket landing problem by converting the KKT conditions into a block-diagonal system and solve it in O(n) time.
Variable Elimination, Smoothing, and Marginalization Explained
1. Explain the variable elimination in an oversimplified way. 2. Explain Fixed-lag smoothing by variable elimination. 3. Discuss a IROS2018 best paper candidate. 4. Some discussion of ISAM2, Semidefinite Programming.
How to Land a rocket? Part 2, Constrained Optimization
Apply constraints to the rocket landing problem. This post gives a introduction to Primal-Dual Interior Point methods.
How to Land a Rocket? Part 1, Problem Definition
Land a rocket 1. Problem formulation and simple tricks.
Lucas-Kanade on Manifolds
Lucas-kanade with SE(2) motion model. We will derive the equations and implement the tracker in C++.
Introduction to Optimization on Manifolds/Lie-groups
A simple example of doing least squares on Manifold. I explained why optimization on Manifold is better and how to do it technically with a solver in Python.