Single Instruction Multiple Data (SIMD), also known as vectorization, is a powerful technique for accelerating computer vision algorithms. In this post, I will explain the concept and then introduce an easy way to use it inside your codes. We will see how we can benefit from SIMD to further reduce the runtime of the Gaussian-blur […]
The future of computer vision and machine learning is toward edge devices. This is why C++ matters. Following my previous post on simple and general tips to optimize C++ codes, I decided to explain further tips that are specified for implementing computer vision algorithms.
The first time I heared its name was 3 years ago in a robotic course. It seemed to be a big complex stuff for me which I tried to escape as much as I could. Soon after building the first ROS application, my interest in it increased such a way that I like to ROS-ify […]
QR codes can store different types of data. Recently, I was involved in a project that a robot had to detect and decode pre-installed QR codes to refine its position. This post explains how I got 10 FPS performance on a Raspberry Pi Zero.
My master thesis was to design and implement a camera-based system for localization of a six-wheeled robot. The computer was a Raspberry Pi 3 which took me a lot of effort to achieve a reasonable performance. This post explains how I got 8-10 FPS localization on KITTI dataset.