References of "Bevilacqua, Vitoantonio"
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See detailA novel approach to evaluate blood parameters using computer vision techniques
Di Maio, Antonio UL; Bevilacqua, Vitoantonio; Marino, Francescomaria et al

in Medical Measurements and Applications (MeMeA), 2016 IEEE International Symposium on (2016, May 15)

Current medical practice for determining hemoglobin concentration (which is especially important for anemic patients in need of blood transfusion) involves frequent blood tests. In this work, we propose ... [more ▼]

Current medical practice for determining hemoglobin concentration (which is especially important for anemic patients in need of blood transfusion) involves frequent blood tests. In this work, we propose an alternative, non-invasive approach to hemoglobin estimation, based on image analysis of a specific conjunctival region. Our ultimate goal is to develop an easy-to-use wearable device that patients themselves can employ at home to autonomously assess their need of blood transfusion. In this paper, we detail the prototype of our device and the methodology for extracting key information from the color values of the acquired image. Tests conducted on 77 anemic and healthy patients show significant correlation between the real hemoglobin value obtained through blood sampling and the value estimated by our algorithm. A prototypical binary classification algorithm for assessing the need of blood transfusion yielded good results in terms of accuracy, specificity and sensitivity, thus making it possible to avoid a significant number of blood tests. [less ▲]

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See detailA computer vision and control algorithm to follow a human target in a generic environment using a drone
Di Maio, Antonio UL; Bevilacqua, Vitoantonio

in Lecture Notes in Computer Science, Intelligent Computing Theories and Application (2016)

This work proposes an innovative technique to solve the problem of tracking and following a generic human target by a drone in a natural, possibly dark scene. The algorithm does not rely on color ... [more ▼]

This work proposes an innovative technique to solve the problem of tracking and following a generic human target by a drone in a natural, possibly dark scene. The algorithm does not rely on color information but mainly on shape information, using the HOG classifier, and on local brightness information, using the optical flow algorithm. We tried to keep the algorithm as light as possible, envisioning its future application on embedded or mobile devices. After several tests, performed modeling the system as a set of SISO feedback-controlled systems and calculating the Integral Squared Error as quality indicator, we noticed that the final performance, overall satisfactory, degrades as the background complexity and the presence of disturbance sources, such as sharp edges and moving objects that cross the target, increase . [less ▲]

Detailed reference viewed: 158 (4 UL)