In this repository I will give some implementation of single and multiple object tracking algorithms. These include meanShift, CamShift, Boosting, MIL, KCF, TLD , GoTurn, and MedianFlow. Additionally I will show you how to grab frames at a very high FPS from camera and videos.

Face Detection and tracking using CamShift, Kalman Filter, Optical Flow

Optimize clustering labels using Silhouette Score.

Mean-shift clustering in Python in 100 lines

Various projects using Open CV

Code/Examples for A New Approach to Robust Estimation of Parametric Structures

Implementation of some of the most used Clustering Algorithms from scratch (only using Numpy)

To track non-rigid objects in a video sequence and keeping the object at the center of the frame by controlling the movement of the camera .

Using the meanshift and optical flow algorithm to trackt objects in RTSP video streams and mp4 video files

Object Tracking

Based on meanshift Algorithm Thoughts, tracking object in video.

base on opencv write in python2.7

Mean-shift clustering algorithm in TensorFlow

Mean shift is a non-parametric feature-space mathematical analysis technique for locating the maxima of a density function, a so-called mode-seeking algorithm.

This repository implements RCNNshift in PyTorch for efficient moving object tracking. RCNNshift enhances the traditional Meanshift tracking algorithm by incorporating an RCNN or 3DRCNN to generate ignition maps, enhancing image channel features for improved tracking.

Image Segmentation Mean shift algorithm. Optimizations included.

Bokeh effect simulator for Image Processing