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SPIE Proceedings, 1988
The Infrared signature of a vehicle is dependent on its surroundings in two ways. First, the vehicle image perceived in an IR scene is directly related to the thermal contrast between the vehicle and its physical environment. Second, the vehicle surface temperature is determined, in part, by the energy exchange at its boundaries which includes the ...
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The Infrared signature of a vehicle is dependent on its surroundings in two ways. First, the vehicle image perceived in an IR scene is directly related to the thermal contrast between the vehicle and its physical environment. Second, the vehicle surface temperature is determined, in part, by the energy exchange at its boundaries which includes the ...
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2016
This chapter contextualizes the role of smart meters in smart grid initiatives around the world to show that the smart grid concept goes beyond energy supplier modernization. In addition, this chapter presents the security model and the privacy model for Privacy-Preserving Protocols (PPPs).
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This chapter contextualizes the role of smart meters in smart grid initiatives around the world to show that the smart grid concept goes beyond energy supplier modernization. In addition, this chapter presents the security model and the privacy model for Privacy-Preserving Protocols (PPPs).
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Background of Pharmacologic Modeling
2013The pharmaceutical industry, which emerged during the second half of the nineteenth century, operates nowadays in a sensitive environment. Providing patients with differentiated medicines that can be afforded by health care systems is proving more and more difficult.
Ronald Gieschke, Daniel Serafin
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Scale-Corrected Background Modeling
2017 14th Conference on Computer and Robot Vision (CRV), 2017Modern security cameras are capable of capturing high-resolution HD or 4K videos and support embedded analytics capable of automatically tracking objects such as people and cars moving through the scene. However, due to a lack of computational power on these cameras, the embedded video analytics cannot utilize the full available video resolution ...
Parthipan Siva, Michael Jamieson
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Aggregated Dynamic Background Modeling
2006 International Conference on Image Processing, 2006Standard practices in background modeling learn a separate model for every pixel in the image. However, in dynamic scenes the connection between an observation and the place where it was observed is much less important and is usually random. For example, a wave observed in an ocean scene could easily have been observed at another place in the image ...
Amit Adam, Ehud Rivlin, Ilan Shimshoni
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Modelling of celestial backgrounds
Sensors and Systems for Space Applications XI, 2018For applications where a sensor’s image includes the celestial background, stars and Solar System Bodies compromise the ability of the sensor system to correctly classify a target. Such false targets are particularly significant for the detection of weak target signatures which only have a small relative angular motion.
Jae-Wan Lim +3 more
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Background modeling for generative image models
Computer Vision and Image Understanding, 2015Discussion of the implicit but unavoidable background model in generative image models.Analysis of common practical strategies to deal with the problem and their drawbacks.Explicit background models are proposed as a fundamental solution.The background model is introduced through an efficient likelihood ratio correction.The background correction ...
Sandro Schönborn +3 more
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2013
Background models are often used in video surveillance systems to find moving objects in an image sequence from a static camera. These models are often built under the assumption that the foreground objects are not known in advance. This assumption has led us to model background using one-class SVM classifiers.
Assaf Glazer +2 more
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Background models are often used in video surveillance systems to find moving objects in an image sequence from a static camera. These models are often built under the assumption that the foreground objects are not known in advance. This assumption has led us to model background using one-class SVM classifiers.
Assaf Glazer +2 more
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Probabilistic Model-based Background Subtraction
2005Usually, background subtraction is approached as a pixel-based process, and the output is (a possibly thresholded) image where each pixel reflects, independent from its neighboring pixels, the likelihood of itself belonging to a foreground object. What is neglected for better output is the correlation between pixels.
Krüger, Volker +2 more
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