Simulation of Object Movement Analysis

Abstract

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. This research project is carried out to determine some of the basic simulation of object motion analysis algorithm that had been founded or developed or even researched and Supports the following types of video sources: AVI files, local capture device .This thesis report would bring a presentation of these algorithms for researchers to get a basic idea of performing an algorithm for simulation of object motion Analysis. One of the most common approaches is to compare the current frame with the previous one. It's useful in video compression when you need to estimate changes and to write only the changes, not the whole frame. But it is not the best one for motion detection applications. If the object is moving smoothly we'll receive small changes from frame to frame. So, it's impossible to get the whole moving object. Things become worse, when the object is moving so slowly, when the algorithms will not give any result at all. I used an image processing library for simplicity, it's not a video processing library. Besides, the library allows me to research different areas more quickly, than to write optimized solutions. I use LDA (Linear Discriminant Analysis) Algorithm for face and object detection. LDA maximizing the component axes for class separation. LDA tries to find projection axes, such as classes are best separated. LDA can be used not only for classification, but also for dimensionality reduction.