Motion Detection Algorithms

There are many approaches for motion detection in a continuous video stream. All of them are based on comparing of the current video frame with one from the previous frames or with something that we ll call background. In this article, I ll try to describe some of the most common approaches.



In descr iption of these algorithms I ll use the AForge.NET framework, which is described in some other articles on Code Project: [1], [2]. So, if you are common with it, it will only help.



The demo application supports the following types of video sources:



• AVI files (using Video for Windows, interop library is included)

• updating JPEG from internet cameras

• MJPEG (motion JPEG) streams from different internet cameras

• local capture device (USB cameras or other capture devices, DirectShow interop library is included). -Motion Detection Algorithms

There are many approaches for motion detection in a continuous video stream. All of them are based on comparing of the current video frame with one from the previous frames or with something that we ll call background. In this article, I ll try to describe some of the most common approaches.



In descr iption of these algorithms I ll use the AForge.NET framework, which is described in some other articles on Code Project: [1], [2]. So, if you are common with it, it will only help.



The demo application supports the following types of video sources:



• AVI files (using Video for Windows, interop library is included)　

• updating JPEG from internet cameras　

• MJPEG (motion JPEG) streams from different internet cameras　

• local capture device (USB cameras or other capture devices, DirectShow interop library is included).