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Most of the stereo-matching algorithms nowadays need high accuracy, especially for objects at large distances. Lots of approaches are able to provide good results at low costs, but at large distances (small disparities) suffer from the so called “pixellocking effect” i.e. an uneven sub-pixel disparity distribution. In order to compensate this effect, developing sub-pixel interpolation functions can...
We propose a method for detecting pedestrians in infrared images. The method combines a fast region of interest generator with fast feature pyramid object detection. Knowing the appearance model of pedestrians in infrared images we infer some edge and intensity based filters that generate the regions in which pedestrian hypotheses may appear. On those regions we apply the Aggregated Channel Features...
Traditionally, subpixel interpolation in stereo-vision systems was designed for the block-matching algorithm. During the evaluation of different interpolation strategies, a strong correlation was observed between the type of the stereo algorithm and the subpixel accuracy of the different solutions. Subpixel interpolation should be adapted to each stereo algorithm to achieve maximum accuracy. In consequence,...
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