Talks and presentations


Computer Vision, Pattern Recognition and Machine Learning (CVPL) 2018

30/31.08.2018 Vico Equense (NA), Italy Presentation

Presentation of my PhD thesis and the activities done in the Perceptual computing and Human Sensing Lab during the biennal meeting of the Italian Association for Computer Vision, Pattern Recognition and Machine Learning (CVPL).


Personality gaze patterns unveiled via automatic relevance determination

25.06.2018 Toulouse, France Conference oral

Presentation of the paper "Personality gaze patterns unveiled via automatic relevance determination" during the 7th International Symposium - From Data to Models and Back (DataMod). In this paper we aim at understanding how the human gaze behaviour in social context, as along a face-to-face interaction, is correlated with personality traits. We propose a different analysis perspective based on novel data-mining techniques and a probabilistic classification method that relies on Gaussian Processes exploiting Automatic Relevance Determination (ARD) kernel.


AMHUSE: A Multimodal dataset for HUmour SEnsing

15.11.2017 Glasgow, UK Conference poster

Presentation of the paper "AMHUSE: A Multimodal dataset for HUmour SEnsing" during the 19th ACM International Conference on Multimodal Interaction. In this paper we present A Multimodal dataset for HUmour SEnsing along with a novel web-based annotation tool named DANTE (Dimensional ANnotation Tool for Emotions). The dataset is the result of an experiment concerning amusement elicitation. Gathered data include RGB video and depth sequences along with physiological responses (electrodermal activity, blood volume pulse, temperature). The videos were later annotated by 4 experts in terms of valence and arousal continuous dimensions. Both the dataset and the annotation tool are made publicly available for research purposes.


Virtual EMG via facial video analysis

11/15.09.2017 Catania, Italy Conference oral

Presentation of the paper "Virtual EMG via facial video analysis" during the 19th International Conference on Image Analysis and Processing. In this paper we propose a method that uses the framework of Gaussian Process regression to predict the facial electromyographic signal from videos where people display non-posed affective expressions. The paper won the Best Paper Award.


A note on modelling a somatic motor space for affective facial expressions

11.09.2017 Catania, Italy Conference oral

Presentation of the paper "A note on modelling a somatic motor space for affective facial expressions" during the 1st Automatic Affect Analysis and Synthesis Workshop. We discuss modelling issues related to the design of a somatic facial motor space. The variants proposed are conceived to be part of a larger system for dealing with simulation-based face emotion analysis along dual interactions.


Affective computing - Domus Academy

14.02.2017 Milan, Italy Lecture

Invited lecture on "Affective computing" as part of the Workshop of Tangible Interaction held by the Master in Interaction Design of Domus Academy.


Machine Learning - opendot

09.11.2016 Milan, Italy Talk

Invited speaker at the opentalk "Machine Learning tra etica, arte e legge", organised by opendot.


The color of smiling: computational synaesthesia of facial expressions

09.09.2015 Genova, Italy Conference poster

Presentation of the paper "The color of smiling: computational synaesthesia of facial expressions" during the 18th International Conference on Image Analysis and Processing. This note gives a preliminary account of the transcoding or rechanneling problem between different stimuli as it is of interest for the natural interaction or affective computing fields. By the consideration of a simple example, namely the color response of an affective lamp to a sensed facial expression, we frame the problem within an information-theoretic perspective.


Using sparse coding for landmark localization in facial expressions

11.12.2014 Paris, Grande Conference poster

Presentation of the paper "Using sparse coding for landmark localization in facial expressions" during the 5th European Workshop on Visual Information Processing. In this article we address the issue of adopting a local sparse coding representation (Histogram of Sparse Codes), in a part-based framework for inferring the locations of facial landmarks. The rationale behind this approach is that unsupervised learning of sparse code dictionaries from face data can be an effective approach to cope with such a challenging problem.