Handbook of Image and Video Processing 2005
DOI: 10.1016/b978-012119792-6/50137-6
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Statistical Models of Targets and Clutter for Use in Bayesian Object Recognition

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Cited by 3 publications
(5 citation statements)
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“…Each template is denoted by I α , to be consistent with the notations used in, 11 where α represents the class of the object α ∈ {car, jeep, tank, plane, . .…”
Section: Mathematics Of Template Transformationsmentioning
confidence: 99%
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“…Each template is denoted by I α , to be consistent with the notations used in, 11 where α represents the class of the object α ∈ {car, jeep, tank, plane, . .…”
Section: Mathematics Of Template Transformationsmentioning
confidence: 99%
“…In the context of ATR, the observation z k can be thought of as an array or a lattice of observed pixel intensities obtained by a camera at time scan k, while x k can be interpreted as the (corresponding) array or lattice of pixel intensities obtained from the hypothesized scene generated using the transformed templates. Physically, the likelihood function serves as the sensor or the measurement model, 9,11 while the prior probability density can be used to set prior distributions for each of the parameters to be estimated. Typically, prior density modeling is relevant for problems where ATR is performed on videos or dynamic scenarios.…”
Section: Problem Formulationmentioning
confidence: 99%
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“…Does visual search mean an algorithm for finding and identifying a specific object or class of objects in an image? The extensive literature on automated target recognition (ATR) exemplifies this philosophy [1]. Or, does visual search imply a general framework for finding information from visual data, but without object-specific guidance?…”
Section: Introductionmentioning
confidence: 99%
“…Does visual search mean an algorithm for finding and identifying a specific object or class of objects in an image? The extensive literature on automated target recognition (ATR) exemplifies this philosophy 1 . Or, does visual search imply a general framework for finding information from visual data without object-specific guidance?…”
Section: Introductionmentioning
confidence: 99%