NDLI: Fusion of global and local information for object detection

Content Provider	IEEE Xplore Digital Library
Author	Garg, A. Agarwal, S. Huang, T.S.
Copyright Year	2002
Description	Author affiliation: Beckman Inst. for Adv. Sci. & Technol., Illinois Univ., Urbana, IL, USA (Garg, A.)
Abstract	This paper presents a framework for fusing together global and local information in images to form a powerful object detection system. We begin by describing two detection algorithms. The first algorithm uses independent component analysis to derive an image representation that captures global information in the input data. The second algorithm uses a part-based representation that relies on local properties of the data. The strengths of the two detection algorithms are then combined to form a more powerful detector The approach is evaluated on a database of real-world images containing side views of cars. The combined detector gives distinctly superior performance than each of the individual detectors, achieving a high detection accuracy of 94% on this difficult test set.
Starting Page	723
Ending Page	726
File Size	312276
Page Count	4
File Format	PDF
ISBN	076951695X
ISSN	10514651
DOI	10.1109/ICPR.2002.1048077
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-08-11
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Object detection Independent component analysis Testing Detectors Detection algorithms Pixel Principal component analysis Computer science Image analysis Image databases
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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