Maurizio Pilu

Direct least square fitting of ellipses

This work presents a new efficient method for fitting ellipses to scattered data. Previous algorithms either fitted general conics or were computationally expensive. By minimizing the algebraic distance subject to the constraint 4ac-b/sup 2/=1, the new method incorporates the ellipticity constraint into the normalization factor. The proposed method combines several advantages: It is ellipse-specific, so that even bad data will always return an ellipse. It can be solved naturally by a generalized eigensystem. It is extremely robust, efficient, and easy to implement.

A direct method for stereo correspondence based on singular value decomposition

This paper proposes a new algorithm for matching point features across pairs of images. Despite the well-known combinatorial complexity of the problem, this work shows that an acceptably good solution can be obtained directly by singular value decomposition of an appropriate correspondence strength matrix. The approach draws from the method proposed previously but, besides suggesting its usefulness for stereo matching, in this work a correlation-weighted proximity function is used as correspondence strength to specifically cater for real images.

Ellipse-specific direct least-square fitting

Ellipse fitting is one of the classic problems of pattern recognition and has been subject to considerable attention because of its many applications. This article presents the first direct method for specifically fitting ellipses in the least squares sense. Previous approaches used either generic conic fitting or relied on iterative methods to recover elliptic solutions. The proposed method is (i) ellipse-specific, (ii) directly solved by a generalised eigen-system, (iii) has a desirable low-eccentricity bias, and (iv) is robust to noise. We provide a theoretical demonstration, several examples and the Matlab coding of the algorithm.

Undoing page curl distortion using applicable surfaces

This work is concerned with the reconstruction of the flat state of a curled document or book page when captured face up by a camera. It is reconstructed with the support of sparse depth measurements of its surface. A novel method based on physical modeling of paper deformation with an applicable surface is proposed and a relaxation algorithm is described that allows us to fit this model and unroll it to a plane so as to produce the undistorted document. Some very promising results are shown that confirm that the use of applicable surfaces is the right way to address this problem.

Undoing paper curl distortion using applicable surfaces

The work presented is concerned with the reconstruction of the original undistorted image of a curled document or book when captured face-up by a camera with the support of sparse depth measurements. A novel method based on physically modeling paper deformation with an applicable surface is proposed and a relaxation algorithm is described that allows us to fit it to noisy data and then flatten it in order to produce the final undistorted image. The promising results obtained confirm that the use of applicable surfaces is the right way to address this problem.

Extraction of illusory linear clues in perspectively skewed documents

The article deals with the recovery of illusory linear clues from perspectively skewed documents, with the purpose of using them for rectification. The computational approach proposed implements the perceptual organization principles implicitly used in textual layouts. The numerous examples provided show that the method is robust and viewpoint and scale invariant.

A light-weight text image processing method for handheld embedded cameras

In the past few years we have witnessed the migration of cheap imaging devices into portable and mobile computing appliances such as PDAs and mobile phones. As these devices become ever more powerful in terms of processor speed and memory, new exciting applications and uses are being developed. A particularly useful one is the casual capture of text images for faxing, note taking, OCR, etcetera. This paper describes the image processing pipeline used to enhance images of text captured by a hand-held low-resolution camera, and a fast text extraction method. The main advantages of the approach are its inherent lightweight structure, speed and relative robustness under poor lighting and focus conditions. The computational efficiency (and a careful implementation) of the approach has allowed its deployment in an interactive-time text capture and foreign-text translation demo on a PDA with a VGA camera attachment.

Training PDMs on models: the case of deformable superellipses

Abstract This paper addresses the following problem: How can we make a complicated mathematical shape model simpler while keeping a comparable level of representational power? The proposed solution is to use the original model itself – which represents a class of shapes – to train a Point Distribution Model (PDM). In this paper the idea is applied to the case of deformable superellipses.

Video stabilization as a variational problem and numerical solution with the Viterbi method

This paper presents a new method for video stabilization based on a variational formulation that produces optimally stable sequences independently of the input motion but within the hard constraints imposed by finite sensor size to the maximum allowed compensatory transformation. A practical and fast numerical solution using the Viterbi algorithm is also proposed. The results show the efficacy of the method compared to a class of previous approaches.

A fast and robust image registration method based on an early consensus paradigm

This paper presents a fast and extremely robust feature-based method for planar registration of partly overlapping images; it uses a two-stage robust fitting approach comprising a fast estimation of a transformation hypothesis (that we show is highly likely to be correct) followed by a confirmation and refinement stage. The method is particularly suited for automatic stitching of oversize documents scanned in two or more parts. We show simulations, also supported by practical experiments, that prove both the robustness and computational efficiency of the approach.