Schlüsselwörter: 2D signal theoretic investigation, 3D scene reconstruction, background elimination, Biomedical imaging, cameras, classical medical tomography applications, computerised tomography, elderly people, filtering techniques, health applications, Image reconstruction, Legged locomotion, mathematical analysis, mathematical description, medical image processing, medical tomography, multidimensional spectra, physical disabilities, Radio frequency, reconstruction process, reconstruction quality, Tomography, visual tomographic reconstruction, Visualization

Schlüsselwörter: active safety car project, automobiles, driver assistance systems, image processing, image segmentation, multisensor data fusion, object detection, object segmentation, sensor fusion, series production vehicles, traffic engineering computing

Zusammenfassung: Driver assistance systems support overstrained and affected drivers and become more and more essential for series-production vehicles. Object detection and segmentation is one of the most challenging research topics in this field. In order to warn the driver or automatically break before a potential collision, objects intersecting the path of the host vehicle have to be detected and classified. Most recently developed approaches are based on two dimensional image processing, sometimes in combination with a tracking algorithm associating detections in consecutive frames to one and the same object. Further robustness is achieved by multisensor data fusion, i.e. information by two or more different sensors (e.g. camera and radar data) are fused in order to get a much more reliable result. Another aspect for safety applications is communication between cars, which provides additional sensor locations and thus also requires data fusion technology. Two different approaches for data fusion are proposed and first results are presented.

Bemerkung: CD

Bemerkung: CD, Postersession