NDLI: Scene Segmentation and Pedestrian Classification from 3-D Range and Intensity Images

Content Provider	IEEE Xplore Digital Library
Author	Xue Wei Son Lam Phung Bouzerdoum, A.
Copyright Year	2012
Abstract	This paper proposes a new approach to classify obstacles using a time-of-flight camera, for applications in assistive navigation of the visually impaired. Combining range and intensity images enables fast and accurate object segmentation, and provides useful navigation cues such as distances to the nearby obstacles and obstacle types. In the proposed approach, a 3-D range image is first segmented using histogram thresholding and mean-shift grouping. Then Fourier and GIST descriptors are applied on each segmented object to extract shape and texture features. Finally, support vector machines are used to recognize the obstacles. This paper focuses on classifying pedestrian and non-pedestrian obstacles. Evaluated on an image data set acquired using a time-of-flight camera, the proposed approach achieves a classification rate of 99.5%.
Starting Page	103
Ending Page	108
File Size	717772
Page Count	6
File Format	PDF
ISBN	9781467316590
ISSN	19457871
DOI	10.1109/ICME.2012.167
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-09
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Cameras Histograms Noise Feature extraction Vectors Navigation assistive navigation range image intensity image segmentation classification
Content Type	Text
Resource Type	Article

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