Journal ArticleDOI
Recursive 3-D road and relative ego-state recognition
E.D. Dickmanns,B.D. Mysliwetz +1 more
TLDR
The general problem of recognizing both horizontal and vertical road curvature parameters while driving along the road has been solved recursively and a differential geometry representation decoupled for the two curvature components has been selected.Abstract:
The general problem of recognizing both horizontal and vertical road curvature parameters while driving along the road has been solved recursively. A differential geometry representation decoupled for the two curvature components has been selected. Based on the planar solution of E.D. Dickmanns and A. Zapp (1986) and its refinements, a simple spatio-temporal model of the driving process makes it possible to take both spatial and temporal constraints into account effectively. The estimation process determines nine road and vehicle state parameters recursively at 25 Hz (40 ms) using four Intel 80286 and one 386 microprocessors. Results with the test vehicle (VaMoRs), which is a 5-ton van, are given for a hilly country road. >read more
Citations
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Dissertation
Bayesian Inference for Automotive Applications
TL;DR: This thesis model the prior of a radar map by a Poisson process which allows it to incorporate the uncertainties in the number of landmarks, their states and data association hypotheses, into the model and derive the exact theoretical batch multi-object posterior density of the map and use Gibbs sampling method to approximate the posterior.
Proceedings ArticleDOI
A global and local condensation for lane tracking
TL;DR: A new condensation filtering algorithm that combines local and global information for tracking of lane markings and multiple image features are fused to weight particles to demonstrate the robustness of this approach.
Dissertation
Model-driven and Data-driven Approaches for some Object Recognition Problems
TL;DR: A model-driven and data-driven approach to obtaining object descriptors that are largely preserved across certain sources of variations, by utilizing models for image formation and local image features and Analyzing the robustness of local feature descriptors to different illumination conditions.
Proceedings ArticleDOI
Fast vision-based vehicle detection algorithm using recognition of light pattern
Sung-Chang Kim,Tae-Sun Choi +1 more
TL;DR: A vehicle detection framework which aims at avoiding collision and warning the dangerous situation during driving on a road at night and using several image processing techniques is presented.
Proceedings ArticleDOI
A novel approach to the enhancement of lane estimator by using Kalman filter
Moonhyung Song,Chang-il Kim,Jong Min Kim,Kwang Soo Lee,Hyun-Bae Park,Jaeseok Jeon,Su-Jin Kwag,Moon-Sik Kim +7 more
TL;DR: A novel approach of lane estimator for more robust curvature information is proposed with Kalman filter and shows that robustness of the proposedlane estimator even in failure situation of front camera is shown.
References
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Journal ArticleDOI
Estimation of Object Motion Parameters from Noisy Images
Ted J. Broida,Rama Chellappa +1 more
TL;DR: An approach is presented for the estimation of object motion parameters based on a sequence of noisy images that may be of use in situations where it is difficult to resolve large numbers of object match points, but relatively long sequences of images are available.
Journal ArticleDOI
Dynamic monocular machine vision
Ernst D. Dickmanns,Volker Graefe +1 more
TL;DR: A new approach to real-time machine vision in dynamic scenes is presented based on special hardware and methods for feature extraction and information processing using integral spatio-temporal models that by-passes the nonunique inversion of the perspective projection by applying recursive least squares filtering.
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