Tracking Methods

Open CV: http://www.intel.com/technology/computing/opencv/

This is a C based library that can be used directly in C code to track moving objects, from first viewing of the project it seems to find regions of interest and track them. The idea behind this is using a filter over an image and taking the gradient values at each window, trying to detect possible regions of interest the video shows an example of a labeled result. This is quite noisy however and should i use it i would need to ensure parameters are set to help specifcy this for the application to remove or at least lower the effects of noise in the image.

Videos: Input and Output




Use: I intend to use this if possible to help give me possible locations for the targets and therefore create bounding boxes of the image so that processing does not need to be calculated for an entire image.

============================================================


Kalman Filters: Kalman filters offer a way of predicting possible error changes from measured data to give us a discription of a true result using probabilty and knowledge of the movement or abilities of the object being tracked. A former lecturer of mine Andrew Calway (University of Bristol) showed me a case study in the case of tracking objects using Kalman filters with a moving camcorder. It can achieve this by finding the object in one location to start with and given possible information about movement uses probability to look in certain expected positions for the target in question, it also considers error margins in these calculations. Thus saving searching an entire image for a target if it has been previously identified.

"The purpose of a Kalman filter is to estimate the state of a system from meaurements which contain random errors. An example is estimating the position and velocity of a satelite from radar data."

Benefits: A further benefit of Kalman filters is that it seems to have a toolbox available directly in matlab currently. This is a major bonus as Matlab will be essential for some fo the high powered matrix operations i will doubtlessly have to perform for varying image processing/segmentation and classification issues related with the project.

Papers: Video Object Tracking Using Region Split And Merge And A Kalman Filter Tracking Algorithm


Video:


Use: I propose to use a kalman filter technique to improve the accuracy of the bounding box of the target found using opencv and be able to predict where the target may occur in the next image. By doing so i can reduce computayional overhead and hopefully lower processing costs too. Thus giving me a smaller problem to work with which is localized to a bounding box of the image.