Computer Vision


Innovation for Data Elaboration in Heritage and Arts

Nov 2018 – Apr 2021
Funded by: MIUR – PON | CNR
IDEHA will create an open IT platform for Cultural Heritage, combining both digital content from traditional repositories and information generated in real time by users or environmental sensors; aggregating, processing and understanding the data by utilizing new learning technologies to build services that can be used by different users profiled through specific multimodal applications.

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Real time video creation according to your emotions

funded by: Regione Toscana | CYNNY S.P.A.
MORPHCAST is an innovative application made by the innovative SME CYNNY S.p.a. that personnalises video contents in real time leveraging the emotional state of the viewer. The system is able to run on both mobile and desktop platforms through a web browser. The profiling is done using information obtained only from the user’s face, such as age, gender, expressed emotions, arousal, valence, head position and 30+ features. To obtain such information, a face analysis system was implemented, together with a “full stack” of computer vision and deep learning algorithms to extract the user pose and estimate demographic information. The aim of this project is to optimize the stack to run in javascript inside of a browser.

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Small Pixels

Small yet beautiful

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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Improving the customer experience in stores by intelligent computer vision

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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