Vectorisation of sketched drawings using co-occurring sample circles

This paper presents a drawing vectorisation algorithm which uses multiple concentric families of circles placed in a dense grid on the image space. We show that any off-centered junction within the family of circles can be located and hence show how these junction points may be linked to neighbouring junction points, thereby creating a vector representation of the drawing geometry. The proposed algorithm identified 98%98% of the junctions in the drawings on which it was evaluated, each within a localisation error of 4.7±2.34.7±2.3 pixels, resulting in straight line vectors which are well placed with respect to the drawn edges.peer-reviewe

Model-free head pose estimation based on shape factorisation and particle filtering

This work forms part of the project Eye-Communicate funded by the Malta Council for Science and Technology through the National Research & Innovation Programme (2012) under Research Grant No. R&I-2012-057.Head pose estimation is essential for several applications and is particularly required for head pose-free eye-gaze tracking where estimation of head rotation permits free head movement during tracking. While the literature is broad, the accuracy of recent vision-based head pose estimation methods is contingent upon the availability of training data or accurate initialisation and tracking of specific facial landmarks. In this paper, we propose a method to estimate the head pose in real time from the trajectories of a set of feature points spread randomly over the face region, without requiring a training phase or model-fitting of specific facial features. Conversely, without seeking specific facial landmarks, our method exploits the sparse 3-dimensional shape of the surface of interest, recovered via shape and motion factorisation, in combination with particle filtering to correct mistracked feature points and improve upon an initial estimation of the 3-dimensional shape during tracking. In comparison with two additional methods, quantitative results obtained through our model- and landmark-free method yield a reduction in the head pose estimation error for a wide range of head rotation angles.peer-reviewe

Multiscale blood vessel delineation using B-COSFIRE filters

We propose a delineation algorithm that deals with bar-like structures of different thickness. Detection of linear structures is applicable to several fields ranging from medical images for segmentation of vessels to aerial images for delineation of roads or rivers. The proposed method is suited for any delineation problem and employs a set of B-COSFIRE filters selective for lines and line-endings of different thickness. We determine the most effective filters for the application at hand by Generalized Matrix Learning Vector Quantization (GMLVQ) algorithm. We demonstrate the effectiveness of the proposed method by applying it to the task of vessel segmentation in retinal images. We perform experiments on two benchmark data sets, namely DRIVE and STARE. The experimental results show that the proposed delineation algorithm is highly effective and efficient. It can be considered as a general framework for a delineation task in various applications.peer-reviewe