SeeForMe on TechCrunch Real-time Wearable Computer Vision System

SeeForMe. Wearable Computer Vision System

Our demo paper “Real-time Wearable Computer Vision System for Improved Museum Experience” at ACM Multimedia 2016 was reported on TechCrunch as worth highlighting!

Read the paper!

SeeForMe is a mobile application which runs on a mobile wearable device and perform real-time object classification and artwork recognition using a wearable device. SeeForMe improves user experience during a museum visit by providing contextual information and performing user profiling.

In the demo paper we propose the use of a compact CNN network that performs object classification and artwork localization and, using the same CNN features, we perform a robust artwork recognition.

Shape based filtering, artwork tracking and temporal filtering further improve recognition accuracy.

Best Poster ACM ICMR 2020

Image Retrieval Using Multi-Scale CNN Feature Pooling

Human Behavior Understanding

by Prof. Mohamed Daoudi

Most cited researchers

Prof Alberto Del Bimbo and Prof. Andrew D. Bagdanov

Tiberio Uricchio

PhD Thesis Award

In 2016 it goes to Tiberio Uricchio, MICC Researcher