Fast Projective Image Rectification for Planar Objects with Manhattan Structure
This method addresses the problem of accurately rectifying images of planar objects like documents or building facades for applications such as document analysis or surgical orientation estimation, but it is incremental as it builds on existing Manhattan World assumptions.
The paper tackles metric rectification of planar objects with Manhattan structure by estimating vanishing points and camera rotation, achieving accuracy better or equal to state-of-the-art on the MIDV-500 dataset when background occupies no more than half the image, with a runtime of about 3ms.
This paper presents a method for metric rectification of planar objects that preserves angles and length ratios. An inner structure of an object is assumed to follow the laws of Manhattan World i.e. the majority of line segments are aligned with two orthogonal directions of the object. For that purpose we introduce the method that estimates the position of two vanishing points corresponding to the main object directions. It is based on an original optimization function of segments that estimates a vanishing point position. For calculation of the rectification homography with two vanishing points we propose a new method based on estimation of the camera rotation so that the camera axis is perpendicular to the object plane. The proposed method can be applied for rectification of various objects such as documents or building facades. Also since the camera rotation is estimated the method can be employed for estimation of object orientation (for example, during a surgery with radiograph of osteosynthesis implants). The method was evaluated on the MIDV-500 dataset containing projectively distorted images of documents with complex background. According to the experimental results an accuracy of the proposed method is better or equal to the-state-of-the-art if the background occupies no more than half of the image. Runtime of the method is around 3ms on core i7 3610qm CPU.