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Vincenzo Santopietro

Researcher at University of Naples Federico II

Publications -  9
Citations -  1172

Vincenzo Santopietro is an academic researcher from University of Naples Federico II. The author has contributed to research in topics: Video tracking & CUDA. The author has an hindex of 4, co-authored 9 publications receiving 893 citations. Previous affiliations of Vincenzo Santopietro include University of Salerno.

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Book ChapterDOI

The sixth visual object tracking VOT2018 challenge results

Matej Kristan, +158 more
TL;DR: The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative; results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years.
Proceedings ArticleDOI

The Visual Object Tracking VOT2017 Challenge Results

Matej Kristan, +104 more
TL;DR: The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative; results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years.
Book ChapterDOI

Using GPGPU Accelerated Interpolation Algorithms for Marine Bathymetry Processing with On-Premises and Cloud Based Computational Resources

TL;DR: An innovative implementation of the Inverse Distance Weight (IDW) interpolation algorithm leveraging on CUDA GPGPUs is presented, related to high resolution bathymetry interpolation in a crowdsource data context.
Journal ArticleDOI

Watch Out: Embedded Video Tracking with BST for Unmanned Aerial Vehicles

TL;DR: The paper presents the development of a real time tracking system that is able to efficiently run on an Nvidia Jetson board mounted on a UAV (Unmanned Aerial Vehicle) that can track almost every possible target in real time.

Embedded Deep Learning for Face Detection and Emotion Recognition with Intel© Movidius (TM) Neural Compute Stick

TL;DR: This work focused on two main tasks, that have gained significant attention from researchers, that are automated face detection and emotion recognition, and shows how inference can be accelerated using Intel’s Neural Compute Stick.