Motion Detection using Mixture of Gaussians for Wildlife Photography

Wildlife photography triggers can be easy to distinguish when using lighting and background distractions but can be a challenge when using motion detection. With the MoG model, the detection can be enhanced which also helps when it comes to modeling the background and capture effectively the stationary object and moving object with better clarity. This type of photography usually requires one to take photos of animals without disturbing their natural function. The MoG method helps us to capture them separately from the background (static image or video) as well as correctly identifying animal movements. This project uses a motion detection system based on the Mixture of Gaussians (MoG) algorithm to help improve wildlife photography. The system can go one step further when employing motion detection, instead of leaving it up to the user to click the shutter, it automatically triggers the camera when it detects movement, significantly reducing the human presence, and increasing the chance of a timely and clean capture.