Presentation 2015-03-20
A study on construction of pedestrian detectors adaptive to driving environment referring to false detection tendency
Yuki SUZUKI, Daisuke DEGUCHI, Ichiro IDE, Hiroshi MURASE,
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Abstract(in English) Recently, safety driving assistance systems using an in-vehicle camera have been studied actively. In particular, since pedestrian detection by image processing is an important task, various methods have been proposed. In real environment, appearance of pedestrians varies largely due to the difference of driving environments such as weather condition, time, driving scene, etc. Therefore, it is difficult to handle all driving scene by a single detector. This report focuses on the false detection tendency according to various driving environments, and constructs pedestrian detectors adaptive to each environment. By applying a conventional pedestrian detector to an in-vehicle camera image, false detections specific to each driving environment are obtained. By referring to these false detections, the proposed method constructs pedestrian detectors adaptive to a driving environment, and they are used for improving the detection accuracy. We conducted experiments using a public dataset to evaluate the proposed method. As a result, accuracy of the proposed method was improved in comparison with a conventional pedestrian detector.
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Keyword(in English) adaptive learning / false positive tendency / pedestrian detection
Paper # BioX2014-67,PRMU2014-187
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Conference Information
Committee PRMU
Conference Date 2015/3/12(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A study on construction of pedestrian detectors adaptive to driving environment referring to false detection tendency
Sub Title (in English)
Keyword(1) adaptive learning
Keyword(2) false positive tendency
Keyword(3) pedestrian detection
1st Author's Name Yuki SUZUKI
1st Author's Affiliation Graduate School of Information Science, Nagoya University()
2nd Author's Name Daisuke DEGUCHI
2nd Author's Affiliation Information and Communications Headquarters, Nagoya University
3rd Author's Name Ichiro IDE
3rd Author's Affiliation Graduate School of Information Science, Nagoya University
4th Author's Name Hiroshi MURASE
4th Author's Affiliation Graduate School of Information Science, Nagoya University
Date 2015-03-20
Paper # BioX2014-67,PRMU2014-187
Volume (vol) vol.114
Number (no) 521
Page pp.pp.-
#Pages 6
Date of Issue