Fast reducing perspective distortion for road marking recognition

Feng, Min; Fang, Bin; Wu, Yang

doi:10.1109/itsc.2017.8317821

Cited by 2 publications

(2 citation statements)

References 17 publications

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“…By deriving (10), (11) and 18, we have established a relationship between the projections of the points in space before and after rotation. These are fundamental equations to perform any projective rotation.…”

Section: Projective Rotation In 3dmentioning

confidence: 99%

“…There are many sorts of perspective effects causing this aberrant appearance of the targets in the scene. Understanding these phenomena has long been an interesting topic for artists, designers and researchers, and various cases have to be taken into consideration; for example, in image diagnostic [11], monitoring [12], photogrammetry, object reconstruction [13], character reconstruction [14], [15] and pose estimation [16]- [18]. According to Aloimonos in [19], there are three different independent effects which describe perspective distortion.…”

Section: Introductionmentioning

confidence: 99%

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Perspective Distortion Modeling for Image Measurements

et al. 2020

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A perspective distortion modelling for monocular view that is based on the fundamentals of perspective projection is presented in this work. Perspective projection is considered to be the most ideal and realistic model among others, which depicts image formation in monocular vision. There are many approaches trying to model and estimate the perspective effects in images. Some approaches try to learn and model the distortion parameters from a set of training data that work only for a predefined structure. None of the existing methods provide deep understanding of the nature of perspective problems. Perspective distortions, in fact, can be described by three different perspective effects. These effects are pose, distance and foreshortening. They are the cause of the aberrant appearance of object shapes in images. Understanding these phenomena have long been an interesting topic for artists, designers and scientists. In many cases, this problem has to be necessarily taken into consideration when dealing with image diagnostics, high and accurate image measurement, as well as accurate pose estimation from images. In this work, a perspective distortion model for every effect is developed while elaborating the nature of perspective effects. A distortion factor for every effect is derived, then followed by proposed methods, which allows extracting the true target pose and distance, and correcting image measurements.

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Section: Projective Rotation In 3dmentioning

confidence: 99%