There are 2 repositories under camshift topic.
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
Computer Vision model to detect face in the first frame of a video and to continue tracking it in the rest of the video. This is implemented in OpenCV 3.3.0 and Python 2.7
Autonomous drone using detected ball to command the direction of the drone
Various projects using Open CV
YOLOv5+DeepSORT and Camshift+Kalman
Face Detection and tracking using CamShift, Kalman Filter, Optical Flow
Multi-Agent Visual Tracking Project based on CamShift
C++ refinement of PedestrianCounter.
Using the meanshift and optical flow algorithm to trackt objects in RTSP video streams and mp4 video files
Tracking object from video using cv2
OpenCV demonstrations of selected algorithms related to motion tracking: (1) mean shift, (2) CAMSHIFT, (3) iterative Lucas-Kanade algorithm with pyramids, and (4) Farnebäck's algorithm
Computer Vision model to detect face in the first frame of a video and to continue tracking it in the rest of the video. This is implemented in OpenCV 3.3.0 and Python 2.7
base on opencv write in python2.7
The AR related project was developed in the period of exchange student in University of Tsukuba.
CAMSHIFT, a colour based tracking system, and a Non-Photorealistic Rendering application. Created during 2013 Nuffield Placement at Glasgow Caledonian University.
homework;course:Image acquisition and processing;goal:tracking a colorful object