The aim of this thesis is to explore different methods for helping computers interpret the real world visually, investigate solutions to those methods offered by the open-sourced computer vision library, OpenCV, and implement some of these in a Raspberry Pi based application for detecting and keeping track of objects. The main focus rests on the practical side of the project. The result of this thesis is a GNU/Linux based C/C++ application that is able to detect and keep track of objects by reading the pixel values of frames captured by the Raspberry Pi camera module. The application also transmits some useful information, such as coordinates and size, to other computers on the network that send an appropriate query. The source code of the program is documented and can be developed further.