IAS-LAB PUBLICATIONS
W2613733732
Authors: AREA MIN. 09 - Ingegneria industriale e dell'informazione; Non assegn; 2015-06-05T01:02:04Z
Published: title_year
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Authors: AREA MIN. 09 - Ingegneria industriale e dell'informazione; Non assegn; ITA; 2015-06-05T02:59:42Z; 9788890042621
Published: MATCH_RESULT_STATUS_FAILURE_NO_MATCH
W2137030978
Authors: Non assegn; AREA MIN. 09 - Ingegneria industriale e dell'informazione; 2015-06-05T02:55:28Z; 9788890042621
Published: title_year
scopus.description.allpeopleoriginal
Authors: 232 NIEUWE HEMWEG 6B, 1013 BG AMSTERDAM, NETHERLANDS; eng 2-s2.0-34548256473
Journal: Italy||Italy||Italy||Italy||Italy||Japan||Italy
Published: 18
Volume: Menegatti E.; Simionato C.; Tonello S.; Cicirelli G.; Distante A.; Ishiguro H.; Pagello E. Pages: Menegatti||Simionato||Tonello||Cicirelli||Distante||Ishiguro||Pagello-In this paper an omnidirectional Distributed Vision System (DVS) is presented. The presented DVS is able to learn to navigate a mobile robot in its working environment without any prior knowledge about calibration parameters of the cameras or the control law of the robot (this is an important feature if we want to apply this system to existing camera networks). The DVS consists of different Vision Agents (VAs) implemented by omnidirectional cameras. The main contribution of the work is the explicit distribution of the acquired knowledge in the DVS. The aim is to develop a totally autonomous system able not only to learn control policies by on-line learning, but also to deal with a changing environment and to improve its performance during lifetime. Once an initial knowledge is acquired by one Vision Agent, this knowledge can be transferred to other Vision Agents in order to exploit what was already learned. In this paper, first we investigate how the Vision Agent learns the knowledge, then we evaluate its performance and test the knowledge propagation on three different VAs. Experiments are reported both using a system simulator and using a prototype of the Distributed Vision System in a real environment demonstrating the feasibility of the approach.
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Authors: 518 HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY; eng 2-s2.0-38049173172
Journal: Italy||Italy||Italy||Italy
Published: false
Volume: Lastra A.; Pretto A.; Tonello S.; Menegatti E. Pages: Lastra||Pretto||Tonello||Menegatti-Detection of human skin in an arbitrary image is generally hard. Most color-based skin detection algorithms are based on a static color model of the skin. However, a static model cannot cope with the huge variability of scenes, illuminants and skin types. This is not suitable for an interacting robot that has to find people in different rooms with its camera and without any a priori knowledge about the environment nor of the lighting. In this paper we present a new color-based algorithm called VR filter. The core of the algorithm is based on a statistical model of the colors of the pixels that generates a dynamic boundary for the skin pixels in the color space. The motivation beyond the development of the algorithm was to be able to correctly classify skin pixels in low definition images with moving objects, as the images grabbed by the omnidirectional camera mounted on the robot. However, our algorithm was designed to correctly recognizes skin pixels with any type of camera and without exploiting any information on the camera. In the paper we present the advantages and the limitations of our: algorithm and we compare its performances with the principal existing skin detection algorithms on standard perspective images. © Springer-Verlag Berlin Heidelberg 2007.
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Authors: 398 5 TOH TUCK LINK, SINGAPORE 596224, SINGAPORE; eng 2-s2.0-34247369856
Journal: Italy||Italy||Italy||Italy||Italy
Published: false
Volume: Menegatti E.; Cavasin M.; Pagello E.; Mumolo E.; Nolich M. Pages: Menegatti||Cavasin||Pagello||Mumolo||Nolich-This paper presents a Distributed Perception System for application of intelligent surveillance. The system prototype presented in this paper is composed of a static acoustic agent and a static vision agent cooperating with a mobile vision agent mounted on a mobile robot. The audio and video sensors distributed in the environment are used as a single sensor to reveal and track the presence of a person in the surveilled environment. The robot extends the capabilities of the system by adding a mobile sensor (in this work an omnidirectional camera). The mobile omnidirectional camera can be used to have a closer look of the scene or to inspect portions of the environment not covered by the fix sensory agents. In this paper, the hardware and the software architecture of the system and of its sensors are presented. Experiments on the integration of the audio localization data and on the video localization data are reported. © World Scientific Publishing Company.
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Authors: + 345 E 47TH ST, NEW YORK, NY 10017 USA; eng 2-s2.0-67649739175
Journal: Italy||Japan||Japan||Japan||Italy||Italy
Published: IEEE Computer Society
4813893
Volume: Libera F.D.; Minato T.; Fasel I.; Ishiguro H.; Menegatti E.; Pagello E. Pages: Libera||Minato||Fasel||Ishiguro||Menegatti||Pagello-This paper investigates touching as a natural way for humans to communicate with robots. In particular we developed a system to edit motions of a small humanoid robot by touching its body parts. This interface has two purposes: it allows the user to develop robot motions in a very intuitive way, and it allows us to collect data useful for studying the characteristics of touching as a means of communication. Experimental results confirm the interface's ease of use for inexpert users, and analysis of the data collected during human-robot teaching episodes has yielded several useful insights. © 2008 IEEE.
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Authors: + AVENIDA D MANUEL L, 27A 2 ESQUERDO, SETUBAL, 2910-595, PORTUGAL; eng 2-s2.0-58149140239
Journal: Italy||Italy||Italy||Italy
Published: MATCH_RESULT_STATUS_FAILURE_NO_MATCH
Volume: Gasperin A.; Ardito C.; Grisan E.; Menegatti E. Pages: Gasperin||Ardito||Grisan||Menegatti-In image-based robot navigation, the robot localises itself by comparing images taken at its current position with a set of reference images stored in its memory. The problem is then reduced to find a suitable metric to compare images, and then to store and compare efficiently a set of images that grows quickly as the environment widen. The coupling of omnidirectional image with Fouriersignature has been previously proved to be a viable framework for image-based localization task, both with regard to data reduction and to image comparison. In this paper, we investigate the possibility of using a space variant camera, with the photosensitive elements organised in a log polar layout, thus resembling the organization of the primate retina. We show that an omnidirectional camera using this retinal camera, provides a further data compression and excellent image comparison capability, even with very few components in the Fourier signature.
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Authors: 538 345 E 47TH ST, NEW YORK, NY 10017 USA; eng 2-s2.0-67649687094
Journal: Italy||Italy||Italy
Published: IEEE Computer Society
DOI: University of Padua||University of Padua||ISIB-CNR
4813922
Volume: Pretto A.; Menegatti E.; Pagello E. Pages: Pretto||Menegatti||Pagello-This paper describes a visual feature detector and descriptor scheme designed to address the specific problems of humanoid robots in the tasks of visual odometry, localization, and SLAM (Simultaneous Localization And Mapping). During walking, turning, and squatting movements, the camera of a humanoid robot moves in jerky and sometimes unpredictable way. This causes an undesired motion blur in the images grabbed by the robot camera, that negatively affects the performance of the image processing algorithms. Indeed, the classical features detector and descriptor filtering techniques, that proved to work so well for wheeled robots, do not perform so reliably in humanoid robots. This paper presents a method to detect image interest points (invariant to scale transformation and rotations) robust to motion-blur introduced by the camera motion. Our approach is based on a preprocessing step to estimate the Point Spread Function (PSF) of the motion blur. The PSF is used to deconvolve the image reducing the blur. Then, we apply a feature detector inspired by SURF approach and the feature descriptor from SIFT. Experiments performed on standard datasets corrupted with motion blur and on images taken by a camera mounted on a small humanoid robot show the effectiveness of the proposed technique. Our approach presents higher performances and higher reliability in matching features in the different images of a sequence affected by motion-blur. © 2008 IEEE.
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Authors: AREA MIN. 10 - Scienze dell'antichita,filologico-letterarie e storico-artistiche; 2015-06-05T01:32:11Z; 9788886868204
Published: MATCH_RESULT_STATUS_FAILURE_NO_MATCH