In this thesis, we improve a sliding-window based object detector by a local alignment of evaluated sub-windows. In order to achieve real-time performance on high-resolution images, the detector needs to operate on a relatively sparse grid, which however decreases its recognition
performance. The proposed local alignment improves its recognition performance whilst retaining the necessary speed. The proposed method is tested on a car detection problem.