A new anti-aliasing approach for improved motion-based object detection using linear filters

In this paper a new anti-aliasing approach for motion-based object detection using linear shift invariant (LSI) filters is presented. Mainly originating from the field of signal processing, LSI-filter-based motion detection has been topic of research for a long time, though due to low computational power of contemporary computers the developed systems have been unfeasible for application in mass products like driver assistance systems. However, recent progress in hardware in conjunction with decreasing costs makes using linear filters a very interesting alternative of increasing performance of common approaches. One of the most important factors falsifying object detection results obtained using linear shift invariant (LSI) is aliasing. This is mostly caused by the low temporal resolution of the camera signal which leads to the fact that the sampling theorem does not hold for objects moving at high speed in the image plane. In general, aliasing errors cannot be removed after sampling. Under certain conditions, however, their impact on the filter result can be successfully decreased using the approach presented in this paper. The applicability of the new approach is demonstrated using scenes recorded by a camera installed in a blind spot warning system.