NDLI: Feature based person detection beyond the visible spectrum

Content Provider	IEEE Xplore Digital Library
Author	Kai Jungling Arens, M.
Copyright Year	2009
Description	Author affiliation: FGAN-FOM, Ettlingen, Germany (Kai Jungling; Arens, M.)
Abstract	One of the main challenges in computer vision is the automatic detection of specific object classes in images. Recent advances of object detection performance in the visible spectrum encourage the application of these approaches to data beyond the visible spectrum. In this paper, we show the applicability of a well known, local-feature based object detector for the case of people detection in thermal data. We adapt the detector to the special conditions of infrared data and show the specifics relevant for feature based object detection. For that, we employ the SURF feature detector and descriptor that is well suited for infrared data. We evaluate the performance of our adapted object detector in the task of person detection in different real-world scenarios where people occur at multiple scales. Finally, we show how this local-feature based detector can be used to recognize specific object parts, i.e., body parts of detected people.
Starting Page	30
Ending Page	37
File Size	1182085
Page Count	8
File Format	PDF
ISBN	9781424439942
ISSN	21607508
DOI	10.1109/CVPRW.2009.5204085
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Infrared detectors Computer vision Shape Motion segmentation Layout Object detection Cameras Motion detection Image sequences Application software
Content Type	Text
Resource Type	Article

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