lucas-kanade

High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀

Taking a Deeper Look at the Inverse Compositional Algorithm (CVPR 2019, Oral)

Problem Set solutions for the "Introduction to Computer Vision (ud810)" MOOC from Udacity

Optical Flow estimation in pure Python

A generic pipeline to align multimodal image pairs from different sensors by extending Lucas-Kanade on feature maps. CVPR2021

Robust Local Optical Flow (RLOF)

Vehicle speed estimation using the optical flow algorithm from a mono camera(CCTV)

Implementation of Lucas Kanade Tracking system using six parameter affine model and recursive Gauss-Newton process.

C++/CUDA solutions, slides, and resources for Udacity's Intro to Computer Vision (UD810) course.

C++ implementation of Lucas-Kanade-Image-Alignment

Implementation for our CVPR 2021 oral paper "PointNetLK Revisited".

video stabilization: stabilize the videos which is taken from wavering camera. Image mosaicing: stitches multiple, overlapping snapshot images of a video together in order to produce one large image.

The swiss army knife for extracting optical flow

Determining optical flow by using Horn-Schunck method and Lucas-Kanade method

An implementation of optical flow using both the Lucas Kanade method as well as Horn Schunck.

This repo includes solutions to all the 'in the class quizzes' and 7 problem sets of the Introduction to Computer Vision course (G Tech CS6476 - on Udacity)

Implementation of Lucas-Kanade tracker algorithm to track a moving car, face of a baby and running Usain Bolt

Official Python Implementation for "CycleLK: Self-Supervised Cycle Lucas-Kanade Network for Correspondence Flow", In Submission

A C CUDA implementation of the Lucas Kanade Optical Flow Algorithm

Lucas Kanade optical flow generator

In this repository, we deal with the task of video frame interpolation with estimated optical flow. To estimate the optical flow we use Lucas-Kanade algorithm, Multiscale Lucas-Kanade algorithm (with iterative tuning), and Discrete Horn-Schunk algorithm. We explore the interpolation performance on Spheres dataset and Corridor dataset.

[ECE NTUA] Image & Video Analysis - Programming Sets & Solutions (2020-2021)

Consist of four different approaches for generating optical flow and can be demonstrated in Colab.

Optical Flow and Deep Learning Use Cases

The goal of this project is to implement the keypoint detector FAST (Features from Accelerated Segment Test) and to track keypoints with the Kanade–Lucas–Tomasi feature tracker.

A Lucas-Kanade implementation

Lucas-Kanade tracking demo

Lucas Kanade digital image correlation.