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High-resolution remote sensing images can capture detailed geometrical and shape properties. Traditional classification accuracy assessments with overall accuracy or kappa coefficient based on pixels, cannot exhibit the geometrical properties of the objects that are present on the ground. Evaluation of object oriented classified maps based on geometrical and border information can provide more accurate...
We propose a method that detects and segments multiple, partially occluded objects in images. A part hierarchy is defined for the object class. Whole-object segmentor and part detectors are learned by boosting shape oriented local image features. During detection, the part detectors are applied to the input image. All the edge pixels in the image that positively contribute to part detection responses...
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