A Unified Framework for Concurrent Pedestrian and Cyclist Detection
In this paper we present a vision-based detection system for cyclists. We build cascaded detectors with different classifiers and shared features to detect cyclists from multiple viewpoints. To improve the performance, we reveal the dependence between the size and the position of an object in the image by a regression method. We also explore the applications of this geometric constraint with different camera setups. Based on experiments we demonstrate that our detector is suitable for real time applications.