Arcangelo Bruna - Academia.edu (original) (raw)

Papers by Arcangelo Bruna

International Conference on Computer Vision Theory and Applications, 2013

Discriminating smooth image regions from areas in which significant signal activity occurs is a w... more Discriminating smooth image regions from areas in which significant signal activity occurs is a widely studied subject and is important in low level image processing as well as computer vision applications. In this paper we present a novel method for estimating signal activity in an image directly in the CFA (Color Filter Array) Bayer raw domain. The solution is robust against noise in that it utilizes low level noise characterization of the image sensor to automatically compensate for high noise levels that contaminate the image signal.

— The widespread diffusion of hand-held devices with video recording capabilities requires the ad... more — The widespread diffusion of hand-held devices with video recording capabilities requires the adoption of reliable Digital Stabilization methods to enjoy the acquired sequences without disturbing jerkiness. In order to effectively get rid of the unwanted camera movements, an estimate of the global motion between adjacent frames is necessary. This paper presents a novel approach for estimating the global motion between frames using a Curve Warping technique known as Dynamic Time Warping. The proposed algorithm guarantees robustness also in presence of sharp illumination changes and moving objects 1. Index Terms —Video Stabilization, Dynamic Time Warping, global motion estimation. I.

2020 International Joint Conference on Neural Networks (IJCNN)

The goal of this paper is to develop a Brain Computer Interface (BCI) based on voluntary eye blin... more The goal of this paper is to develop a Brain Computer Interface (BCI) based on voluntary eye blinks decoding. In particular, the study was focused on the signals generated in the cortex by eye blinking, which can be collected by frontopolar scalp Electroencephalographic (EEG) sensors. Normally, EEG recording systems meant for clinical applications are expensive and cannot be used in large-scale user-friendly applications. Thanks to a prototype made by the STMicroelectronics company, based on an Open Source EEG project, a low-cost EEG recording system was created in this work. The goal is to develop an algorithm that can detect and discriminate between voluntary (forced) and involuntary (natural) blinking so that, in the future, an EEG-based BCI system that is able to control a device through eye movements could be developed, which would be of great use for all people with motor disabilities who can control eye movements. The proposed algorithm is based on a one-dimensional (1D) Convolutional Neural Network (CNN) architecture. Frontopolar EEG signals were collected during the execution of voluntary and spontaneous blinks by four healthy subjects. A dataset of EEG epochs of including blinks was constructed and used to train and validate the proposed CNN. The proposed system allowed to discriminate the blinks performed by the subjects (voluntary vs. involuntary) with an average accuracy of 97.92%.

Image Processing for Embedded Devices

Journal of Electronic Imaging

To avoid grabbing the unintentional user motion in a video sequence, video stabilization techniqu... more To avoid grabbing the unintentional user motion in a video sequence, video stabilization techniques are used to obtain better-looking video for the final user. We present a low power rototranslational solution, extending our previous work specifically addressed for translational motion only. The proposed technique achieves a high degree of robustness with respect to common difficult conditions like noise perturbations, illumination changes, and motion blurring. Moreover, it is also able to cope with regular patterns, moving objects and it is very precise, reaching about 7% of improvement in jitter attenuation, compared to previous results. Overall performances are competitive also in terms of computational cost: it runs at more than 30 frames∕s with VGA sequences, with a CPU ARM926EJ-S at just 100 MHz clock frequency.

2020 International Joint Conference on Neural Networks (IJCNN), 2020

This document describes an advanced system and methodology for Cross Traffic Alert (CTA), able to... more This document describes an advanced system and methodology for Cross Traffic Alert (CTA), able to detect vehicles that move into the vehicle driving path from the left or right side. The camera is supposed to be not only on a vehicle still, e.g. at a traffic light or at an intersection, but also moving slowly, e.g. in a car park. In all of the aforementioned conditions, a driver’s short loss of concentration or distraction can easily lead to a serious accident. A valid support to avoid these kinds of car crashes is represented by the proposed system. It is an extension of our previous work, related to a clustering system, which only works on fixed cameras. Just a vanish point calculation and simple optical flow filtering, to eliminate motion vectors due to the car relative movement, is performed to let the system achieve high performances with different scenarios, cameras and resolutions. The proposed system just uses as input the optical flow, which is hardware implemented in the p...

In the last decade, automotive companies have invested a lot in terms of innovation about many as... more In the last decade, automotive companies have invested a lot in terms of innovation about many aspects regarding the automatic driver assistance systems. One innovation regards the usage of a smart camera placed on the car’s side mirror for monitoring the back and lateral road situation. A common road scenario is the overtaking of the preceding car and, in this case, a brief distraction or a loss of concentration can lead the driver to undertake this action, even if there is an already overtaking vehicle, leading to serious accidents. A valid support for a secure drive can be a smart camera system, which is able to automatically analyze the road scenario and consequentially to warn the driver when another vehicle is overtaking. This paper describes a method for monitoring the side view of a vehicle by using camera optical flow motion vectors. The proposed solution detects the presence of incoming vehicles, assesses their distance from the host car, and warns the driver through diffe...

2021 7th International Conference on Automation, Robotics and Applications (ICARA)

This document describes a novel low-cost methodology called “Towards and Tangent” for point to po... more This document describes a novel low-cost methodology called “Towards and Tangent” for point to point navigation in robotics systems. The system navigates in an unknown environment, and it avoids obstacles to reach the desired point, using only laser range sensor, without any integration with mems or another kind of data. It is composed by two simple steps: head toward the goal and select the direction with the lower angle to overcome the obstacle. In this way, compared to the state of the art algorithms, it requires less computational resources, since it does not need to detect obstacles discontinuities and do not need to follow an obstacle's boundaries. Moreover, a simple state machine can handle both obstacle avoidance and point to point navigation. Even if the system is easy to implement and requires low resources, it reaches high performances, in line with more sophisticated algorithms and works very well in real-time.

Journal of Visual Communication and Image Representation, 2017

We introduce a set of distortion adaptive Sobel filters for the direct estimation of geometricall... more We introduce a set of distortion adaptive Sobel filters for the direct estimation of geometrically correct gradients of wide angle images. The definition of the filters is based on Sobel's rationale and accounts for the geometric transformation undergone by wide angle images due to the presence of radial distortion. Moreover, we show that a local normalization of the filters magnitude is essential to achieve stateof-the-art results. To perform the experimental analysis, we propose an evaluation pipeline and a benchmark dataset of images belonging to different scene categories. Experiments on both, synthetic and real images, show that our approach outperforms the current state-of-the-art in both gradient estimation and keypoint matching for images characterized by large amounts of radial distortion. The collected dataset and the MATLAB code of the proposed method can be downloaded at our web page http://iplab.dmi.unict. it/DASF/.

IEEE Transactions on Image Processing, 2017

Perspective cameras are the most popular imaging sensors used in Computer Vision. However, many a... more Perspective cameras are the most popular imaging sensors used in Computer Vision. However, many application fields including automotive, surveillance and robotics, require the use of wide angle cameras (e.g., fisheye), which allow to acquire a larger portion of the scene using a single device at the cost of the introduction of noticeable radial distortion in the images. Affine covariant feature detectors have proven successful in a variety of Computer Vision applications including object recognition, image registration and visual search. Moreover, their robustness to a series of variabilities related to both the scene and the image acquisition process has been thoroughly studied in the literature. In this paper, we investigate their effectiveness on fisheye images providing both theoretical and experimental analyses. As theoretical outcome, we show that the inherently non-linear radial distortion can be locally approximated by linear functions with a reasonably small error. The experimental analysis builds on Mikolajczyk's benchmark to assess the robustness of three popular affine region detectors (i.e., Maximally Stable Extremal Regions (MSER), Harris and Hessian affine region detectors), with respect to different variabilities as well as to radial distortion. To support the evaluations, we rely on the Oxford dataset and introduce a novel benchmark dataset comprising 50 images depicting different scene categories. Experiments are carried out on rectilinear images to which radial distortion is artificially added, and on real-world images acquired using fisheye lenses. Our analysis points out that affine region detectors can be effectively employed directly on fisheye images and that the radial distortion is locally modelled as an additional affine variability.

2015 IEEE International Conference on Image Processing (ICIP), 2015

In this paper we tackle the problem of correctly estimating the gradient of distorted images. The... more In this paper we tackle the problem of correctly estimating the gradient of distorted images. The proper estimation of the gradient in the presence of distortion is of great interest due to the large number of applications relying on wide angle cameras (e.g., in surveillance, automotive, robotics). To this aim we propose the Generalized Sobel Filters (GSF), a family of adaptive Sobel filters able to correctly estimate the gradient of distorted images. To assess the performances of the proposed method, we acquired a benchmark dataset of high resolution images belonging to different categories which are relevant to application domains where the gradient estimation is usually employed. We build an objective evaluation pipeline and perform experiments which show that our method outperforms the state-of-the-art.

Advanced Concepts for Intelligent Vision Systems, 2015

When in a pipeline a robust global motion estimation is needed, RANSAC algorithm is the usual cho... more When in a pipeline a robust global motion estimation is needed, RANSAC algorithm is the usual choice. Unfortunately, since RANSAC is an iterative method based on random analysis, it is not suitable for real-time processing. This paper presents an outlier removal algorithm, which reaches a robust estimation at least equal to RANSAC with really low power consumption and can be employed for embedded time implementation.