Interactively refining object-recognition system

Existing techniques for object recognition often make use of a combination of multiple algorithms and sensors to achieve adequate results. In this paper we propose a real-time system to efficiently combine multiple object-recognition techniques, appropriate for mobile Augmented Reality applications. We focus on the challenge to differentiate objects with only marginal distinguishing features that can often only be identified from specific points of view, and solve this problem by interactively guiding the user during the recognition process. The system is based on a hierarchy to organize model data and control the corresponding feature-detection techniques as shown in a prototypical implementation. Furthermore, recognition techniques are chosen based on context information, e.g. feature type, reliability of sensor data, etc