The field of image processing is gaining more and more importance in our world. As computing power becomes more cheap and available, several different real-time object tracking solutions are being made available.
The most obvious and well-known field of real-time image processing is automated navigation, but remotely related industries as commercial advertising can benefit from image recognition, too. When a company creates an advertisement video, or uses product placement to gain publicity through movies or TV shows, the actual time a given trademark appeared on air needs to be tracked to provide measurements with which the fulfillment of a contract can be controlled.
I designed a tool with the goal of performing real-time trademark matching using the combination of two very different object tracking algorithms, augmented with prediction and filtering of measurements.
Trying to achieve real-time performance on high-definition image sequences with a frame rate of 25 FPS, I examined the possibilities of parallel programming, and implemented parts of my software to utilize the power of modern parallel computing devices.