Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Otto Lohlein"'
Publikováno v:
Intelligent Vehicles Symposium
With the help of advanced driver assistance systems (ADAS), today's vehicles are already able to perform impressive perception tasks. Besides information about other traffic participants, the current environmental visibility condition is one key aspe
Autor:
Martin Fritzsche, Otto Lohlein
Publikováno v:
Subsurface Sensing Technologies and Applications. 1:247-267
The detection of buried anti-personnel mines (APMs) is widely considered as a problem which may only be solved with a combination of two or more complementary sensors. We present processing and fusion results obtained from a multisensor data set, acq
Autor:
Martin Fritzsche, Raimar Wagner, Klaus Dietmayer, Antje Westenberger, Otto Lohlein, Michael Gabb
Publikováno v:
ITSC
This paper addresses the problem of monocular vehicle detection for forward collision warning. We present a system that is able to process large images with high speed and delivers high detection rates at only one false alarm every 100 frames.
Publikováno v:
Intelligent Vehicles Symposium
Vision-based driver assistance systems have great potential for preventing fatalities. This work addresses the problem of 3D monocular vehicle tracking and turn rate estimation in situations where vehicles need to be tracked along intersections and c
Publikováno v:
Intelligent Systems: Models and Applications ISBN: 9783642339585
The precise localization of pedestrians in images is a difficult problem with many practical applications in the fields of driver assistance, autonomous vehicles and visual surveillance. Localization can be treated as a subsequent step to pedestrian
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a2ba81db43bfafcaa9f391a33941d693
https://doi.org/10.1007/978-3-642-33959-2_17
https://doi.org/10.1007/978-3-642-33959-2_17
Autor:
Otto Lohlein, Roland Schweiger, Michael Gabb, Raimar Wagner, Markus Gressmann, Oliver Hartmann, Klaus Dietmayer
Publikováno v:
ICCE-Berlin
For object detection in monocular images, the Boosted Cascade [1] has become the standard approach for driver assistance systems. This paper studies the discriminative power of different features for common automotive object detection tasks: pedestri
Autor:
Otto Lohlein, Matthias Serfling
Publikováno v:
Transportation Technologies for Sustainability
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::43b3f08358bb988337216d0f71fc9592
https://doi.org/10.1007/978-1-4419-0851-3_782
https://doi.org/10.1007/978-1-4419-0851-3_782
Publikováno v:
Advances in Intelligent and Soft Computing ISBN: 9783642294600
Belief Functions
Belief Functions
This contribution presents the design of an image-based contextual pedestrian classifier for an automotive application. Our previous work shows that local classifiers working with image cutouts are in many cases not sufficient to achieve satisfactory
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d81112b75c96eaf030b228cac3da0107
https://doi.org/10.1007/978-3-642-29461-7_37
https://doi.org/10.1007/978-3-642-29461-7_37
Publikováno v:
ITSC
Pedestrian detection is of particular interest to the automotive domain, where an accurate estimation of a pedestrian's position is the first step towards reliable collision avoidance systems. Driven by rapid advances in technology, several systems t
Publikováno v:
2011 IEEE 9th International Symposium on Intelligent Systems and Informatics.