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Robust Unstructured Road Detection: The Importance of Contextual Information : Identificazione robusta di percorsi non strutturati: l'importanza delle informazioni contestuali, in: International Journal of Advanced Robotic Systems |
Documenti accessibili
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Informazioni generali |
| Autore |
Shang, Erke; An, Xiangjing; Li, Jian; Ye, Lei; He, Hangen |
| Pubblicato |
InTech Open Access Publisher, 2013
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| Abstract |
Unstructured road detection is a key step in an
unmanned guided vehicle (UGV) system for road
following. However, current vision‐based unstructured
road detection algorithms are usually affected by
continuously changing backgrounds, different road types
(shape, colour), variable lighting conditions and weather
conditions. Therefore, a confidence map of road
distribution, one of contextual information cues, is
theoretically analysed and experimentally generated to
help detect unstructured roads. Two traditional
algorithms, support vector machine (SVM) and k‐nearest
neighbour (KNN), are carried out to verify the
helpfulness of the proposed confidence map. Following
this, a novel algorithm, which combines SVM, KNN and
the confidence map under a Bayesian framework, is
proposed to improve the overall performance of the
unstructured road detections. The proposed algorithm
has been evaluated using different types of unstructured
roads and the experimental results show its effectiveness. |
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International Journal of Advanced Robotic Systems
Autore: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Publié: 2004
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