High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
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Updated
Jul 25, 2024 - Python
High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
Taking a Deeper Look at the Inverse Compositional Algorithm (CVPR 2019, Oral)
A generic pipeline to align multimodal image pairs from different sensors by extending Lucas-Kanade on feature maps. CVPR2021
Problem Set solutions for the "Introduction to Computer Vision (ud810)" MOOC from Udacity
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
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.
C++/CUDA solutions, slides, and resources for Udacity's Intro to Computer Vision (UD810) course.
Implementation of Lucas-Kanade tracker algorithm to track a moving car, face of a baby and running Usain Bolt
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
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.
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