This thesis investigates a new form of search engine, which enables the user to search for objects in the real world, just like traditional search engines locate resources on the Internet. A search engine for the real world is a step towards an Internet of Things, where real-world objects become visible to computer systems. In order to being nonintrusive, the tracking of objects is done using visual object detection. It is examined whether instrumenting the environment or instrumenting the user is more convenient in order to ubiquitously integrate a real-world search-engine into the daily life of a user. To explore those questions, two prototypes are developed and two user studies are conducted. A stationary prototype called Antonius, which instruments the environment, is built. It implements a web-based frontend and a two-dimensional map for representing the location of real-world objects. As a result of the user study, a second mobile prototype called mobile Antonius is built, which instruments the user instead of the environment. It additionally implements a 3D model of the surveyed area to represent the location of sought objects. The results introduce three categories of users represented as personas, which outline the participants’ thoughts. Although a visual object detection-based real-world search engine decreases the user’s privacy, the user study showed that people are still willing to use such a system for the benefit of never losing an object again. As a result of this research, the mobile system is found to be more convenient regarding privacy and intrusiveness. As well as providing a useful service, the results reveal many promising application areas in personalization, targeting and ubiquitous computing.