amithlawrence94,Amith Lawrence,github

👋 Hi, I’m Amith Lawrence
👀 I’m interested in Network Optimization, 0-RAN, SDN orchestration and Computer Vision related technologies
🌱 I’m currently learning SDN and NFV virtualization
💞️ I’m looking to collaborate on unsupervised machine learning projects
📫 If you are interested and want to contact me, then email me @ [email protected]

Amith Lawrence's Projects

Gaussian and Laplacian pyramid reconstruction, Multi resolution blending, Detector & Descriptor, Homography matrix(translation and rotation parameters, Image stitching is performed by using SIFT and BF matcher

homebrew-core

🍻 Default formulae for the missing package manager for macOS

motion-estimation

Motion Estimation- Optical flow(Pyramidal Lucas Kanade) and Descriptor matching(FAST&FREAK,FAST&LUCID) Implementation in C++ Readme file This project implements the following methods and compares their working FAST for detecting key points and FREAK as descriptor FAST for detecting key points and LUCID as descriptor FAST for detecting key points and optical flow(Lucas-Kane) as descriptor These methods are used for motion estimation of vehicles. Compiling and running instructions: 1.Open the code in eclipse aide 2.create configurable target for the project( right click on the project and select build targets then create. Then type the target name as project name and select OK.) 3.click on the build targets and double click on the target with project name to build it. 4.open terminal from the release folder of the project. 5. Type ./project_name to execute it. Results: time for fast + freak : 4.78 time for fast + lucid : 4.66 time optical flow : 5.52 This zip folder contains Project_FF - contains code and input files for FAST + FREAK Project_FL - contains code and input files for FAST + LUCID Project_LKopt - contains code and input files for FAST + optical flow output - folder consists of output samples of the project 1. outputFF - output of FAST + FREAK 2. outputFL - output of FAST + LUCID 3. outputFF - output of FAST + optical flow PDF report. System specification: Macbook Air - 128GB SSD and 8GB RAM. Processor - core i5 OS - 64 bit UBUNTU 18.04 LTS. s