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

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

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

Optical Flow estimation in pure Python

Robust Local Optical Flow (RLOF)

An implementation of several tracking algorithms based on Lucas Kanade algorithms

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

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

Optical Flow and Deep Learning Use Cases

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

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.

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)

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

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

The swiss army knife for extracting optical flow

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

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