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Alessandra Fascioli
Researcher at University of Parma
Publications - 51
Citations - 3176
Alessandra Fascioli is an academic researcher from University of Parma. The author has contributed to research in topics: Object detection & Pedestrian detection. The author has an hindex of 25, co-authored 51 publications receiving 3089 citations. Previous affiliations of Alessandra Fascioli include Information Technology University & Volkswagen.
Papers
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Journal ArticleDOI
Vision-based intelligent vehicles: State of the art and perspectives
TL;DR: The most common approaches to the challenging task of Autonomous Road Guidance are surveyed, with the most promising experimental solutions and prototypes developed worldwide using AI techniques to perceive the environmental situation by means of artificial vision.
Journal ArticleDOI
Artificial vision in road vehicles
Massimo Bertozzi,Alberto Broggi,Massimo Cellario,Alessandra Fascioli,Paolo Lombardi,Marco Porta +5 more
TL;DR: This paper surveys the most advanced approaches to (partial) customization of the road following task, using on-board systems based on artificial vision, and describes the functionalities of lane detection, obstacle detection and pedestrian detection.
Proceedings ArticleDOI
Shape-based pedestrian detection
TL;DR: This paper presents the method for detecting pedestrian recently implemented on the ARGO vehicle: the analysis of a monocular image delivers a first coarse detection, while a distance refinement is performed using the stereo vision technique.
Journal ArticleDOI
Stereo inverse perspective mapping: theory and applications
TL;DR: An extension to the inverse perspective mapping geometrical transform to the processing of stereo images and the calibration method used on the ARGO autonomous vehicle is presented.
Book
Automatic Vehicle Guidance: the Experience of the ARGO Autonomous Vehicle
TL;DR: In this paper, the authors present the ARGO prototype vehicle, developed at the University of Parma in Italy and describes its equipment, setup, and performance, including cameras and processing systems.