- Artificial Intelligence, Computer Science, Computer Vision, Image Processing, OOAD, UML, Design Patterns, semantic interoperbility, ontology, serious games, e-learning, computer architectures, computer modelling and behavioural simulation, Particle filters, and 22 moreVisual tracking, Extended Kalman Filter, Sensor Fusion, Multirobot systems, Cooperative Robot Localization, Graph Optimization, Cooperative Object Tracking, Moving Landmarks, Spherical Object Detection, Database Systems, Content Analysis, Localization, Content-Based Image Retrieval, Tagging Technologies, Engineering, Information Technology, Data Mining, Computer Engineering, Software Engineering, Machine Learning, Computer Networks, and Algorithmsedit
- Emanuele Frontoni joined the Dept. of Information Engineering (DII) at the Università Politecnica delle Marche, as a ... moreEmanuele Frontoni joined the Dept. of Information Engineering (DII) at the Università Politecnica delle Marche, as a Ph.D. student in "Intelligent Artificial Systems". He obtained his PhD in 2006 discussing a thesis on Vision Based Robotics. At present he has an Assistant Professor position in the same department. His research focuses on applying artificial intelligence and computer vision techniques to mobile robots. He is a member of IEEE, MESA, GIRPR and AI*IA.edit
Linear buffer strips (BS) along watercourses are commonly adopted to reduce runoff , accumulation of bank-top sediments and the leaking of pesticides into fresh-waters, which strongly increase water pollution. However, the monitoring of... more
Linear buffer strips (BS) along watercourses are commonly adopted to reduce runoff , accumulation of bank-top sediments and the leaking of pesticides into fresh-waters, which strongly increase water pollution. However, the monitoring of their conditions is a difficult task because they are scattered over wide rural areas. This work demonstrates the benefits of using a standard data layer and Augmented Reality (AR) in watershed control and outlines the guideline of a novel approach for the health-check of linear BS. We designed a mobile environmental monitoring system for smart maintenance of riverbanks by embedding the AR technology within a Geographical Information System (GIS). From the technological point of view, the system's architecture consists of a cloud-based service for data sharing, using a standard data layer, and of a mobile device provided with a GPS based AR engine for augmented data visualization. The proposed solution aims to ease the overall inspection process by reducing the time required to run a survey. Indeed, ordinary operational survey conditions are usually performed basing the fieldwork on just classical digitized maps. Our application proposes to enrich inspections by superimposing information on the device screen with the same point of view of the camera, providing an intuitive visualization of buffer strip location. This way, the inspection officer can quickly and dynamically access relevant information overlaying geographic features, comments and other contents in real time. The solution has been tested in fieldwork to prove at what extent this cutting-edge technology contributes to an effective monitoring over large territorial settings. The aim is to encourage officers, land managers and practitioners toward more effective monitoring and management practices.
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Eye tracking technology is becoming easier and cheaper to use, resulting in its increasing application to numerous fields of research. Recent years have seen rapid developments in this area. In light of the foregoing, in the context of... more
Eye tracking technology is becoming easier and cheaper to use, resulting in its increasing application to numerous fields of research. Recent years have seen rapid developments in this area. In light of the foregoing, in the context of Cultural Heritage (CH), the definition of a modern approach to understand how individuals perceive art is challenging. Despite the art perception is highly subjective and variable according to knowledge and experience, more recently, several scientific study and enterprises started to quantify how subjects observe art by the application of the eye-tracking technology. The aim of this study was to understand the visual behaviour of subjects looking at paintings, using eye-tracking technology, in order to define a protocol for optimizing an existing Augmented Reality (AR) application that allows the visualiza-tion of digital contents through a display. The stimuli used are three famous paintings preserved at the National Gallery of Marche (Urbino, Marche Region, Italy). We applied eye-tracking to have a deeper understanding of people visual activities in front of these paintings and to analyse how digital contents eventually influence their behaviour. The description of the applied procedure and the preliminary results are presented .
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Highly accelerated life test (HALT) is a test methodology to evaluate reliability of mechanical and electromechanical devices. HALT is often used on devices that must be guaranteed for high reliability over a long time span. HALT... more
Highly accelerated life test (HALT) is a test
methodology to evaluate reliability of mechanical and
electromechanical devices. HALT is often used on devices
that must be guaranteed for high reliability over a long
time span. HALT simulates the life cycle of the device,
usually until it experiments a failure. HALT tests are used
to assess reliability of devices at the end of the production
cycle, but are also used to improve the design and manufacturing
process, allowing to find and correct potential
problems when changes to the production process are less
costly. HALT tests are usually difficult and time consuming,
and there is a strong need for their automation. This
paper proposes a methodology to design software and
hardware for HALT automated tests. The goals pursued
are to standardize the test process, to reduce the need for
manual commands at the minimum and to simplify the
data gathering process. The methodology proposed starts
from domain requirement analysis and is conceived to
be as general as possible, with the goal to make it easily
extensible and adaptable to multiple testing domains.
Finally, the paper reports on a case study describing a
HALT test device designed according to the proposed
methodology and currently in use to test electromechanical
actuators.
methodology to evaluate reliability of mechanical and
electromechanical devices. HALT is often used on devices
that must be guaranteed for high reliability over a long
time span. HALT simulates the life cycle of the device,
usually until it experiments a failure. HALT tests are used
to assess reliability of devices at the end of the production
cycle, but are also used to improve the design and manufacturing
process, allowing to find and correct potential
problems when changes to the production process are less
costly. HALT tests are usually difficult and time consuming,
and there is a strong need for their automation. This
paper proposes a methodology to design software and
hardware for HALT automated tests. The goals pursued
are to standardize the test process, to reduce the need for
manual commands at the minimum and to simplify the
data gathering process. The methodology proposed starts
from domain requirement analysis and is conceived to
be as general as possible, with the goal to make it easily
extensible and adaptable to multiple testing domains.
Finally, the paper reports on a case study describing a
HALT test device designed according to the proposed
methodology and currently in use to test electromechanical
actuators.
Research Interests:
Automated approaches to building detection in multi-source aerial data are important in many applications, including map updating, city modeling, urban growth analysis and monitoring of informal settlements. This paper presents a... more
Automated approaches to building detection in multi-source aerial data are important in many applications, including map updating, city modeling, urban growth analysis and monitoring of informal settlements. This paper presents a comparative analysis of different methods for automated building detection in aerial images and laser data at different spatial resolutions. Five methods are tested in two study areas using features extracted at both pixel level and object level, but with the strong prerequisite of using the same training set for all methods. The evaluation of the methods is based on error measures obtained by superimposing the results on a manually generated reference map of each area. The results in both study areas show a better performance of the Dempster-Shafer and the AdaBoost methods, although these two methods also yield a number of unclassified pixels. The method of thresholding a normalized DSM performs well in terms of the detection rate and reliability in the less vegetated Mannheim study area, but also yields a high rate of false positive errors. The Bayesian methods perform better in the Memmingen study area where buildings have more or less the same heights.
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This paper aims to propose a novel idea of an embedded intelligent system where low cost embedded vision systems can analyze human behaviors to obtain interac-tivity and statistical data, mainly devoted to customer behavior analysis. In... more
This paper aims to propose a novel idea of an embedded intelligent system where low cost embedded vision systems can analyze human behaviors to obtain interac-tivity and statistical data, mainly devoted to customer behavior analysis. In this project we addressed the need for new services into the shop, involving consumers more directly and instigating them to increase their satisfaction and, as a consequence, their purchases. To do this, technology is very important and allows making interactions between costumers and products and between customers and the environment of the shop a rich source of marketing analysis. We construct a novel system that uses vertical RGBD sensor for people counting and shelf interaction analysis, where the depth information is used to remove the affect of the appearance variation and to evaluate customers' activities inside the store and in front of the shelf, with products. Also group interactions are monitored and analyzed with the main goal of having a better knowledge of the customers' activities, using real data in real time. Even if preliminary, results are convincing and most of all the general architecture is affordable in this specific application, robust, easy to install and maintain and low cost.
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The importance of finding correct correspondences between two images is the major aspect in problems such as appearance-based robot localization and content-based image retrieval. Local feature matching has become a commonly used method... more
The importance of finding correct correspondences between two images is the major aspect in problems such as appearance-based robot localization and content-based image retrieval. Local feature matching has become a commonly used method to compare images, despite being highly probable that at least some of the matchings/correspondences it detects are incorrect. In this paper we describe a novel approach to local feature matching, named Feature Group Matching (FGM), to select stable features and obtain a more reliable similarity value between two images. The proposed technique is demonstrated to be translational, rotational and scaling invariant. Experimental evaluation was performed on large and heterogeneous datasets of images using SIFT and SURF, the actual state-of-art feature extractors. Results show that FGM avoids almost 95% of incorrect matchings, reduces the visual aliasing (number of images considered similar) and increases both robotic localization and image retrieval accuracy on the average of 13%.
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The main goal of the SIT-REM project is the design and the development of an interoperable web-GIS environment for the information retrieval and data editing/updating of the geobotanical and wildlife map of Marche Region. The vegetation,... more
The main goal of the SIT-REM project is the design and the development of an interoperable web-GIS environment for the information retrieval and data editing/updating of the geobotanical and wildlife map of Marche Region. The vegetation, plant landscape OPEN ACCESS ISPRS Int. J. Geo-Inf. 2014, 3 2 and faunistic analysis allow the realization of a regional information system for wildlife-geobotanical data. A main characteristic of the SIT-REM is its flexibility and interoperability, in particular, its ability to be easily updated with the insertion of new types of environmental, faunal or socioeconomic data and to generate analyses at any geographical (from regional to local) or quantitative level of detail. Different query levels obtain the latter: spatial queries, hybrid query builder and WMSs usable by means of a GIS. SIT-REM has been available online for more than a year and its use over this period has produced extensive data about users' experiences.
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The development of reliable and precise indoor localization systems would considerably improve the ability to investigate shopper movements and behavior inside retail environments. Previous approaches used either computer vision... more
The development of reliable and precise indoor localization systems would considerably improve the ability to investigate shopper movements and behavior inside retail environments. Previous approaches used either computer vision technologies or the analysis of signals emitted by communication devices (beacons). While computer vision approaches provide higher level of accuracy, beacons cover a wider operational area. In this paper, we propose a sensor fusion approach between active radio beacons and RGB-D cameras. This system, used in an intelligent retail environment where cameras are already installed for other purposes, allows an affordable environment setup and a low operational costs for customer indoor localization and tracking. We adopted a Kalman filter to fuse localization data from radio signals emitted by beacons are used to track users' mobile devices and RGB-D cameras used to refine position estimations. By combing coarse localization datasets from active beacons and RGB-D data from sparse cameras, we demonstrate that the indoor position estimation is strongly enhanced. The aim of this general framework is to provide retailers with useful information by analyzing consumer activities inside the store. To prove the robustness of our approach, several tests were conducted into a real indoor showroom by analyzing real customers behavior with encouraging results.
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ABSTRACT: Automatic building detection has been a hot topic since the early 1990's. Early approaches were based on a single aerial image. Detecting buildings is a difficult task so it can be more... more
ABSTRACT: Automatic building detection has been a hot topic since the early 1990's. Early approaches were based on a single aerial image. Detecting buildings is a difficult task so it can be more effective when multiple sources of information are obtained and fused. The objective of this paper is to provide a comparative analysis of automatic approaches to building detection from multi-source aerial images. We analysed data related to both urban and suburban areas and took into consideration both object-based and pixel-based ...
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New smart objects to improve the quality of life in the ambient assisted living (AAL) scenario are capturing the interest of researchers and companies. In particular, novel assistive technologies are being developed to make accessible... more
New smart objects to improve the quality of life in the ambient assisted living (AAL) scenario are capturing the interest of researchers and companies. In particular, novel assistive technologies are being developed to make accessible street navigation to impaired people. The solution that we propose in this new application domain of intelligent transportation systems is a framework for a safe point-to-point navigation, owing to high-detailed road graphs, including sidewalks, crosswalks, and generic “obstacles.” The system is based on a low-cost modular sensor box (embedded hardware) interfaced with a mobile/phone application that acts as an intelligent navigator. The main novelty is the capability to sense the surrounding area while being able to perform a fast path replanning, owing to a real-time link to a remote server, if an obstacle is detected. The sensing is performed using different sensors, such as ultrasound, lidar, and a 77-GHz mid-range automotive radar (absolutely novel in the AAL context), which are processed and fused in the well-established robot operating system (ROS). We tested the framework by analyzing its performance in two different configurations and environments by using, respectively, a sonar and a laser rangefinder in a building scenario and a radar in an urban environment. Even if in both cases results demonstrated a quite good robustness in the obstacle detection with a quasi-real-time route replanning, we were mainly interested and succeeded in demonstrating the high flexibility and extensibility of our framework.
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ABSTRACT: Today, one of the main applications of multi-source aerial data is the city modelling. The capability to automatically detect objects of interest starting from LiDAR and multi-spectral data is a complex and an open problem. The... more
ABSTRACT: Today, one of the main applications of multi-source aerial data is the city modelling. The capability to automatically detect objects of interest starting from LiDAR and multi-spectral data is a complex and an open problem. The information obtained can be also used for city planning, change detection, road graph update, land cover/use. In this paper we present an automatic approach to object extraction in urban area; the proposed approach is based on different sequential stages. The first stage basically solves a multi- ...
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ABSTRACT: The specific objective of this paper was to provide a comparative analysis of three automatic classification algorithms: Quinlan's C4. 5 and two robust probabilistic classifiers like Support Vector Machine (SVM) and... more
ABSTRACT: The specific objective of this paper was to provide a comparative analysis of three automatic classification algorithms: Quinlan's C4. 5 and two robust probabilistic classifiers like Support Vector Machine (SVM) and AdaBoost (a short for “adaptive boosting”). This work is part of a wider project whose general objective is to develop a methodology for the automatic classification, based on CORINE land-cover (CLC) classes, of high resolution multispectral IKONOS images. The dataset used for the comparison is ...