The main research during my PhD involved statistical models of pedestrian shape and appearance with an application to on-board pedestrian detection for intelligent vehicles. Rather than deriving an explicit model of human appearance, we follow a pattern classification approach, where appropriate models are implicitly learned from a large number of training examples.
At Daimler R&D, I am responsible for algorithmic development and evaluation of the Daimler vision-based pre-crash pedestrian recognition system. I am further interested in generic object recognition methods and vision-based 3D scene understanding in complex environments.
Keywords: Pedestrian recognition, scene understanding, image processing, machine learning, intelligent vehicles