Computer Vision

Predicting Action Progress

Action understanding and prediction for humans assistance

2018-2019
In this project we address the problem of predicting action progress in videos. This is an extremely important task because, on the one hand, it can be valuable for a wide range of applications and, on the other hand, it facilitates better action detection results.
To solve this problem we introduce a novel approach, named ProgressNet, capable of predicting when an action takes place in a video, where it is located within the frames, and how far it has progressed during its execution.

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GANIMEDE

Object detection and recognition

2018-2019
funded by: Leonardo – Finmeccanica

GANIMEDE is a technology transfer project in collaboration with the Italian multinational aerospace, defense and security company Leonardo. In this project MICC is developing a video analysis framework to detect and recognise objects of security interest.

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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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