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Valentina Vasco

Post Doc
Event-driven vision for the iCub

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IIT Central Research Lab Genova


Via Morego 30, Genova, Italy

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Valentina Vasco is a fellow-PhD at the iCub Facility of the Italian Institute of Technology.
She earned both Bachelor and Master's degree in Biomedical Engineering at the University of Naples, in 2010 and 2013 respectively. During her Master thesis, she exploited machine learning techniques to investigate the use of the electrocardiographic signal as biometric pattern, opposed to conventional systems (fingerprint, iris, voice etc.).

She is currently part of the Neuromorphic Systems and Interfaces group, led by Dr. Chiara Bartolozzi, working on how to exploit event-driven vision for a robust interaction of the iCub with moving objects. Specifically, she has been working on event-based feature detection, in order to extract event-based features unaffected by the aperture problem.

She has also worked on a biological inspired implementation of vergence control for the iCub, based on populations of event-driven Gabor filters, simulating the neural receptive fields of the visual cortex. The results show that a fast and accurate control is achieved, decreasing the latency associated to frame-based cameras, independently on different illumination conditions.

She is currently using the event-based feature detector for motion estimation and independent motion segmentation, in order to remove visual events that appear as a consequence of ego-motion.



Event-driven vision for the iCub

Event-driven cameras are biologically inspired sensors that asynchronously respond to movements that occur in the sensor's field of view, offering low latency and high temporal resolution (both in the order of micro-seconds). As such, they have great potential for fast and low power vision algorithtms for robotics.

Visual motion estimation is a fundamental requirement for the iCub. In the event-space, the motion of an edge is clearly identifiable as slope of events and current techniques for optical flow calculation identify such structures. However, they are affected by the aperture problem, as only the component of the flow vector normal to the primary axis of orientation of the object can be measured. Corner positions are unaffected by aperture problem, as they can be unambiguously tracked over time.

We propose an adaptation of the commonly used Harris corner detector to the event-based data, that processes asynchronously each event whenever the corner moves by a pixel. While event-based data are motion-dependent, the algorithm robustly detects corners regardless their speed, with an error distribution within 2 pixels.














We achieve a computational cost lower than the frame-based counterpart (of ~94%) and at a detection rate proportional to speed. Therefore tracking is possible event for large displacements, as no information is lost (i.e. between frames).



Despite segmenting a moving target from the background is inherently solved by the sensor when it is stationary, cameras mounted on the robot are typically non stationary, as the robot interacts with the surrounding environment. Methods are therefore required to detect independent motion.

We are currently investigating methods for independent motion segmentation, where flow scene statistics (computed only on corners and thus unaffected by the aperture problem) are learnt as function of the robot’s joint velocities when no independently moving objects are present. This allows us to find independently moving objects by comparing the predicted and the actual motion of their corners.

Selected Publications

V. Vasco, A. Glover, and C. Bartolozzi. Fast Event-based Harris Corner Detection Exploiting the Advantages of Event-driven Cameras. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2016), pages 4144–4149, October 2016. [pdf]

V. Vasco, A. Glover, Y. Tirupachuri, F. Solari, M. Chessa, and Bartolozzi C. Vergence control with a neuromorphic iCub. In IEEE-RAS International Conference on Humanoid Robots (Humanoids 2016), November 2016. In press. [pdf]





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I numeri di IIT

L’Istituto Italiano di Tecnologia (IIT) è una fondazione di diritto privato - cfr. determinazione Corte dei Conti 23/2015 “IIT è una fondazione da inquadrare fra gli organismi di diritto pubblico con la scelta di un modello di organizzazione di diritto privato per rispondere all’esigenza di assicurare procedure più snelle nella selezione non solo nell’ambito nazionale dei collaboratori, scienziati e ricercatori ”.

IIT è sotto la vigilanza del Ministero dell'Istruzione, dell'Università e della Ricerca e del Ministero dell'Economia e delle Finanze ed è stato istituito con la Legge 326/2003. La Fondazione ha l'obiettivo di promuovere l'eccellenza nella ricerca di base e in quella applicata e di favorire lo sviluppo del sistema economico nazionale. La costruzione dei laboratori iniziata nel 2006 si è conclusa nel 2009.

Lo staff complessivo di IIT conta circa 1440 persone. L’area scientifica è rappresentata da circa l’85% del personale. Il 45% dei ricercatori proviene dall’estero: di questi, il 29% è costituito da stranieri provenienti da oltre 50 Paesi e il 16% da italiani rientrati. Oggi il personale scientifico è composto da circa 60 principal investigators, circa 110 ricercatori e tecnologi di staff, circa 350 post doc, circa 500 studenti di dottorato e borsisti, circa 130 tecnici. Oltre 330 posti su 1400 creati su fondi esterni. Età media 34 anni. 41% donne / 59 % uomini.

Nel 2015 IIT ha ricevuto finanziamenti pubblici per circa 96 milioni di euro (80% del budget), conseguendo fondi esterni per 22 milioni di euro (20% budget) provenienti da 18 progetti europei17 finanziamenti da istituzioni nazionali e internazionali, circa 60 progetti industriali

La produzione di IIT ad oggi vanta circa 6990 pubblicazioni, oltre 130 finanziamenti Europei e 11 ERC, più di 350 domande di brevetto attive, oltre 12 start up costituite e altrettante in fase di lancio. Dal 2009 l’attività scientifica è stata ulteriormente rafforzata con la creazione di dieci centri di ricerca nel territorio nazionale (a Torino, Milano, Trento, Parma, Roma, Pisa, Napoli, Lecce, Ferrara) e internazionale (MIT ed Harvard negli USA) che, unitamente al Laboratorio Centrale di Genova, sviluppano i programmi di ricerca del piano scientifico 2015-2017.

IIT: the numbers

Istituto Italiano di Tecnologia (IIT) is a public research institute that adopts the organizational model of a private law foundation. IIT is overseen by Ministero dell'Istruzione, dell'Università e della Ricerca and Ministero dell'Economia e delle Finanze (the Italian Ministries of Education, Economy and Finance).  The Institute was set up according to Italian law 326/2003 with the objective of promoting excellence in basic and applied research andfostering Italy’s economic development. Construction of the Laboratories started in 2006 and finished in 2009.

IIT has an overall staff of about 1,440 people. The scientific staff covers about 85% of the total. Out of 45% of researchers coming from abroad 29% are foreigners coming from more than 50 countries and 16% are returned Italians. The scientific staff currently consists of approximately 60 Principal Investigators110 researchers and technologists350 post-docs and 500 PhD students and grant holders and 130 technicians. External funding has allowed the creation of more than 330 positions . The average age is 34 and the gender balance proportion  is 41% female against 59% male.

In 2015 IIT received 96 million euros in public funding (accounting for 80% of its budget) and obtained 22 million euros in external funding (accounting for 20% of its budget). External funding comes from 18 European Projects, other 17 national and international competitive projects and approximately 60 industrial projects.

So far IIT accounts for: about 6990 publications, more than 130 European grants and 11 ERC grants, more than 350 patents or patent applications12 up start-ups and as many  which are about to be launched. The Institute’s scientific activity has been further strengthened since 2009 with the establishment of 11 research nodes throughout Italy (Torino, Milano, Trento, Parma, Roma, Pisa, Napoli, Lecce, Ferrara) and abroad (MIT and Harvard University, USA), which, along with the Genoa-based Central Lab, implement the research programs included in the 2015-2017 Strategic Plan.