Real-Time Tracking of Multiple Objects Using Fiducials for Augmented Reality

Augmented reality requires understanding of the scene to know when, where and what to display as a response to changes in the surrounding world. This understanding often involves tracking and recognition of multiple objects and locations in real-time. Technologies frequently used for multiple object tracking, such as electromagnetic trackers are very limited in range, as well as constraining. The use of Computer Vision to identify and track multiple objects is very promising. However, the requirements for traditional object recognition using appearance-based or model-based vision are very complex and their performance is far from real-time. An alternative is to use a set of markers or fiducials for object tracking and recognition. In this paper we present a system of marker coding that, together with an efficient image processing technique, provides a practical method for tracking the marked objects in real-time. The technique is based on clustering of candidate regions in space using a minimum spanning tree. The markers in the codes also allow the estimation of the three dimensional pose of the objects. We demonstrate the utility of the marker-based tracking technique in an Augmented Reality application. The application involves superimposing graphics over real industrial parts that are tracked using fiducials and manipulated by a human in order to complete an assembly. The system aids in the evaluation of the different assembly sequence possibilities.