In this article, we present a component-based visual tracker for mobile platforms with an application to person tracking. The core of the technique is a component-based descriptor that captures the structure and appearance of a target in a flexible way. This descriptor can be learned quickly from a single training image and is easily adaptable to different objects. It is especially well suited to represent humans since they usually do not have a uniform appearance but, due to clothing, consist of different parts with different appearance. We show how this component-based descriptor can be integrated into a visual tracker based on the well known Condensation algorithm. Several person tracking experiments carried out with a mobile robot in different laboratory environments show that the system is able to follow people autonomously and to distinguish individuals. We furthermore illustrate the advantage of our approach compared to other tracking methods.
展开▼
