Research
My research interests include the fields of event detection and analysis in large scale databases applied to multimedia, semantic analysis and security. During my PhD, I mostly worked on the detection of unexplained activities in a sequence of time-stamped observation data [1, 2], under the supervision of Professors Antonio Picariello, Vincenzo Moscato and V.S. Subrahmanian; more specifically, we defined a general model along with some complex algorithms to detect unexplained activities, and we carried out massive experiments in both video surveillance and cyber-security domains. Afterwards, we have also extended such approach to social network analysis [3].
Since I arrived to Bolzano (May 2015), I have been working on a highly interactive event detection system in the video surveillance context in collaboration with Prof. Sven Helmer. Such system ranges from the generation of raw events to the formulation and the detection of complex high-level events in both offline and online modes. We presented the overall system at CIKM 2017 in Singapore [4]. More specifically, the system is based on an extension of relational algebra, ISEQL (Interval-based Surveillance Event Query Language) - that we defined in a specific paper [5] -, enriched with powerful temporal operators. Such operators are being efficiently integrated into the query processing framework of the PostgreSQL database management system. Moreover, we have recently also adapted and extended ISEQL to fit the requirements of a social network setting. In fact, we have extended the overall event detection framework to allow the detection of high-level events in a social network context [8], for instance abnormal or malicious behavior such as spamming. Additionally, I also worked on a probabilistic approach for itinerary planning with category constraints (in collaboration with Dr. Paolo Bolzoni and Prof. Sven Helmer) [6] , and on a preliminary version of a system including social sensing for improving the user experience in orienteering [7].
One of the goals of my research will deal with the integration of the new ISEQL operators defined for social network context in the query processing framework of the PostgreSQL database management system. Additionally, I also plan to integrate the overall framework for high-level surveillance event detection with a smart robot, in order to enhance the monitoring process. More specifically, the robot will be able to improve the quality of a video stream, which in the earlier work was recorded from a static camera position, by providing a mobile camera, enabling us to get footage from different angles. Furthermore, the robot platform will be able to go beyond just contacting security or the police by taking immediate action when a potentially dangerous event is detected: for instance, picking up an unattended package. Preliminary versions of this framework prototype are shown in [9] and [10]. Then, the following goal would be to improve and extend our prototypical work on event-detection platforms. More specifically, I plan to further increase the efficiency of the data processing components, allowing for faster reaction times and a higher data throughput. Additionally, I want to improve the video capturing capabilities by switching to a multi-camera configuration. Eventually, I plan to replace the Rapiro toy robot that was used for the feasibility studies with more sophisticated hardware to enhance the mobile capabilities of the platform.
Some selected publications are listed in the following:
[1] Massimiliano Albanese, Cristian Molinaro, Fabio Persia, Antonio Picariello, VS Subrahmanian: Finding “unexplained” activities in video. Twenty-Second International Joint Conference on Artificial Intelligence (IJCAI'11), Barcelona, July 2011: 1628-1634.
[2] Massimiliano Albanese, Cristian Molinaro, Fabio Persia, Antonio Picariello, VS Subrahmanian: Discovering the Top-k Unexplained Sequences in Time-Stamped Observation Data. IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume 26, Number 3, 2014: 577-594.
[3] Flora Amato, Aniello Castiglione, Aniello De Santo, Vincenzo Moscato, Antonio Picariello, Fabio Persia, Giancarlo Sperlí: Recognizing human behaviours in online social networks. Computers & Security, Volume 74, 2018: 355-370.
[4] Fabio Persia, Fabio Bettini, Sven Helmer: An Interactive Framework for Video Surveillance Event Detection and Modeling. Proceedings of the 2017 ACM on Conference on Information and Knowledge Management (CIKM’17), Singapore, November 2017: 2515-2518.
[5] Sven Helmer, Fabio Persia: ISEQL: an Interval-based Surveillance Event Query Language. International Journal of Multimedia Data Engineering and Management (IJMDEM), Volume 7, Number 4, 2016: 1-21.
[6] Paolo Bolzoni, Fabio Persia, Sven Helmer: Itinerary Planning with Category Constraints using a Probabilistic Approach. International Conference on Database and Expert Systems Applications (DEXA’17), Lyon, August 2017: 363-377.
[7] Fabio Persia, Sven Helmer, Sergejs Pugacs, Giovanni Pilato: Social Sensing for Improving the User Experience in Orienteering, 2019 IEEE 13th International Conference on Semantic Computing (ICSC ‘19), Newport Beach, California, January 2019: 239-246.
[8] Fabio Persia, Sven Helmer: A Framework for High-Level Event Detection in a Social Network Context Via an Extension of ISEQL, in: IEEE, 2018 IEEE Twelfth International Conference on Semantic Computing (IEEE ICSC 2018), 140-147, (2018).
[9] Daniela D'Auria, Fabio Persia, Fabio Bettini, Sven Helmer, Bruno Siciliano: SARRI: a SmArt Rapiro Robot Integrating a framework for automatic high-level surveillance event detection, in: 2018 Second IEEE International Conference on Robotic Computing (IEEE IRC 2018), 238-241, (2018).
[10] Daniela D'Auria, Fabio Persia, Fabio Bettini, Sven Helmer: Predicting and Preventing Dangerous Events via Video Surveillance Using a Robotic Platform, 2019 Third IEEE International Conference on Robotic Computing (IEEE IRC 2019), 549-554, (2019).