1 September 2001 Contrast model for three-dimensional vehicles in natural lighting and search performance analysis
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Ground vehicles in natural lighting tend to have significant and systematic variation in luminance through the presented area. This arises, in large part, from the vehicle surfaces having different orientations and shadowing relative to the source of illumination and the position of the observer. These systematic differences create the appearance of a structured 3-D object. The 3-D appearance is an important factor in search, figure-ground segregation, and object recognition. We present a contrast metric to predict search and detection performance that accounts for the 3-D structure. The approach first computes the contrast of the front (or rear), side, and top surfaces. The vehicle contrast metric is the area-weighted sum of the absolute values of the contrasts of the component surfaces. The 3-D structure contrast metric, together with target height, account for more than 80% of the variance in probability of detection and 75% of the variance in search time. When false alarm effects are discounted, they account for 89% of the variance in probability of detection and 95% of the variance in search time. The predictive power of the signature metric, when calibrated to half the data and evaluated against the other half, is 90% of the explanatory power.
©(2001) Society of Photo-Optical Instrumentation Engineers (SPIE)
Gary Witus, Grant R. Gerhart, and R. Darin Ellis "Contrast model for three-dimensional vehicles in natural lighting and search performance analysis," Optical Engineering 40(9), (1 September 2001). https://doi.org/10.1117/1.1389867
Published: 1 September 2001
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Cited by 7 scholarly publications.
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KEYWORDS
3D modeling

Target detection

3D acquisition

Data modeling

Error analysis

Received signal strength

3D image processing

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