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Content Provider | IEEE Xplore Digital Library |
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Author | Wixson, L. |
Copyright Year | 1996 |
Description | Author affiliation: David Sarnoff Res. Center, Princeton, NJ, USA (Wixson, L.) |
Abstract | Vision systems that must operate autonomously over varying environmental conditions often must use different parameter values or algorithms depending on these conditions. A key problem is how to automatically assess the incoming imagery to determine these appropriate parameters and algorithms. This paper presents methods for such assessment. Specifically, it presents measures for determining whether the scene is well-lit (i.e. whether objects entire extent is visible, versus just their lights), whether the scene has sufficient contrast, and whether objects are casting shadows. The methods are applied in the domain of traffic monitoring, are based on empirical data, and have been tested on videotape segments from over 25 different scenes. |
Starting Page | 56 |
Ending Page | 62 |
File Size | 750302 |
Page Count | 7 |
File Format | |
ISBN | 081867282X |
ISSN | 10514651 |
DOI | 10.1109/ICPR.1996.546794 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 1996-08-25 |
Publisher Place | Austria |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Lighting Monitoring Layout Vehicle detection Machine vision Cameras Remotely operated vehicles Casting Roads Testing |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition |
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