NDLI: A lazy decision approach based on ternary thresholding for robust target object detection

Content Provider	IEEE Xplore Digital Library
Author	Jae-Yeong Lee Wonpil Yu Jungwon Hwang ChangHwan Kim
Copyright Year	2014
Description	Author affiliation: Center for Bionics, Korea Inst. of Sci. & Technol.(KIST), Seoul, South Korea (Jungwon Hwang; ChangHwan Kim) \|\| Intell. Robot Res. Dept., Electron. & Telecommun. Res. Inst., Daejeon, South Korea (Jae-Yeong Lee; Wonpil Yu)
Abstract	One of the main problems of binary classification of overlapping distributions is that there always exist misclassification errors with any value of threshold. In this paper, we propose a novel lazy decision approach for robust object detection and tracking, where decision on an uncertain observation whose evaluation lies between low and high thresholds is postponed until a clear evidence appears. As a practical application of the proposed approach, we present a sensor fusion pedestrian detection system for safe navigation of UGVs in driving environment. We combine a laser-based detection of target candidates and vision-based evaluation within the proposed lazy decision framework. Experimental results on real test data demonstrate effectiveness of the proposed approach, showing significant improvement of precision-recall performance.
Starting Page	3924
Ending Page	3929
File Size	1592112
Page Count	6
File Format	PDF
ISBN	9781479936854
DOI	10.1109/ICRA.2014.6907428
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-05-31
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sensor fusion Laser fusion Cameras Data processing Detectors Feature extraction
Content Type	Text
Resource Type	Article

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