Presentation | 2008-12-18 Image Sensing Technology of Vision-based Navigation System : The format of Technical Report Zhencheng HU, Keiichi Uchimura, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Human driving is based on the stimulation and perception of the driving environment. IV (Intelligent Vehicle) uses advanced electronic and computer technology to extend human driver's ability of perception, determination and action during driving process to enhance driving safety. As one of the most important feature of intelligent vehicle, vision-based perception technology has widely adopted in lane keeping, obstacle avoidance, pedestrian recognition and other applications. This paper introduces the practice of image sensing technology developed by ITS lab in Kumamoto, in particular, predictable lane recognition for vision-based Car Navigation System (VICNAS) is introduced. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Next generation of car navigation / in-vehicle image sensing / lane recognition / in-vehicle camera market trend |
Paper # | PRMU2008-158 |
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Committee | PRMU |
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Conference Date | 2008/12/11(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Pattern Recognition and Media Understanding (PRMU) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Image Sensing Technology of Vision-based Navigation System : The format of Technical Report |
Sub Title (in English) | |
Keyword(1) | Next generation of car navigation |
Keyword(2) | in-vehicle image sensing |
Keyword(3) | lane recognition |
Keyword(4) | in-vehicle camera market trend |
1st Author's Name | Zhencheng HU |
1st Author's Affiliation | Graduate School of Science and Technology, Kumamoto University() |
2nd Author's Name | Keiichi Uchimura |
2nd Author's Affiliation | Graduate School of Science and Technology, Kumamoto University |
Date | 2008-12-18 |
Paper # | PRMU2008-158 |
Volume (vol) | vol.108 |
Number (no) | 363 |
Page | pp.pp.- |
#Pages | 2 |
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