Computer Vision

I-Mall

Improving the customer experience in stores by intelligent computer vision

2019
Partnership with: University of Salerno, University of Verona, University of Palermo
Funded by: MIUR Ministero of Education, University and Research
The project addresses on computer vision and deep learning for person tracking and profiling mainly inside a shopping Mall. The final project’s application is the analysis of the customer’s behavior to provide personalized suggestions at digital signage terminals. The primary goal is to investigate key scientific computer vision issues that are central to such and similar applications and develop innovative solutions with respect to the state of the art.

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FREEWAY

Face Recognition and Body Re-identification in the Wild

2016-2019
funded by: Leonardo – Finmeccanica

FREEWAY is a technology transfer project in collaboration with the Italian multinational aerospace, defense and security company Finmeccanica. In this project MICC is transferring its know-how in state-of-the-art computer vision for face and full-body recognition and re-identification.

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Small Pixels

Small yet beautiful

2019
Authors: Tiberio Uricchio, Leonardo Galteri, Lorenzo Seidenari, Marco Bertini, Alberto Del Bimbo

Small Pixels stems from research expertise in improving the quality of compressed videos that has been developed over time by the team of proposing members and from trials that have produced encouraging results. Having verified through participation in conferences and events, both the real need of the market for effective solutions and the limited number of valid solutions currently available, the team felt that they could initiate an academic spinoff that after a start-up phase, aimed at the realization of a competitive product, is able to position itself on the international market.

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eSERVANT

People counting, flow analysis, smart mobility, social networking.

Versione Italiana

eSERVANT. Project co-financed under Tuscany POR FESR 2014-2020. Analysing, monitoring and connecting people in large facilities. The eSERVANT project was led by QUID Informatica S.p.A and was carried out in collaboration with the partners Sokom srl, Sintra Consulting srl, Magenta S.R.L. and the DIISM of the University of Siena.

eSERVANT. Operazione/Progetto finanziato nel quadro del POR FESR Toscana 2014-2020. Sviluppo di un sistema di analisi, monitoraggio e raccomandazione di persone in occasione di eventi che si svolgono in grandi strutture.

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