Video Image Segmentation and Object Detection Using Markov Random Field Model and EM Algorithm

With many application in various domains, object detection and tracking has received a great deal of attention over the decades in the field of image analysis and computer vision. It has been studied by scientists from different areas of psychophysical sciences and those from different areas of computer science. However, developing a computer algorithm to do the same thing is one of the toughest tasks in computer vision. Research over the past several years enables similar such as foreground detection, detecting connecting regions, extracting object features. Correspondence-based object matching, detecting left and removed objects. This research paper gives a review of different object detection techniques which are available as of today. The focus is on the segmentation techniques by investigating the use of image frames. The motion based, spatiotemporal, temporal are under segmentation techniques. We incorporate the EM algorithm with these segmentation techniques for better performance of detecting and tracking of an object in this research paper.