Towards an Automatic Blind Spot Camera: Robust Real-time Pedestrian Tracking from a Moving Camera

In this paper, we present a real-time pedestrian tracker that combines a robust appearance-based pedestrian detector with application-specific constraints and motion information. The targeted application is the automatic detection of vulnerable road users in blind spot cameras on trucks. This application imposes several challenges that need to be tackled. Vulnerable road users are a very diverse class, and we need a high precision and recall rate with real-time performance. Here, we present a first step towards such an automatic detection system. The novelty of our approach is the extension of a robust pedestrian detector towards real-time performance. The information from the appearance-based detector is used in combination with motion-based estimations to efficiently reduce the search space for the appearance-based detector in consecutive frames. This results in a multi-pedestrian tracker from a moving camera which is both optimized in terms of accuracy and speed. We recorded several data sequences to evaluate our pedestrian tracker, and performed initial experiments with promising results.