NICORA E.

In this paper we investigate the potential of a family of efficient filters – the Gray-Code Kernels – for addressing visual saliency estimation guided by motion. Our implementation relies on the use of 3D kernels applied to overlapping blocks of frames and is able to gather meaningful spatio-temporal information with a very light computation....

In this paper, we investigate the potential of a family of efficient filters—the Gray-Code Kernels (GCKs)—for addressing visual saliency estimation with a focus on motion information. Our implementation relies on the use of 3D kernels applied to overlapping blocks of frames and is able to gather meaningful spatio-temporal information with a...

Human action recognition from visual data is a popular topic in Computer Vision, applied in a wide range of domains. State-of-the-art solutions often include deep-learning approaches based on RGB videos and pre-computed optical flow maps. Recently, 3D Gray-Code Kernels projections have been assessed as an alternative way of representing motion,...

In this work we discuss the action classification performance obtained with a baseline assessment of the MoCA dataset: a multimodal, synchronised dataset including Motion Capture data and multi-view video sequences of upper body actions in a cooking scenario. To this purpose, we setup a classification pipeline to manipulate the two data type....

In this paper we present the tangible coding activity we proposed as an interactive laboratory at the Festival della Scienza in Genova, Italy, in 2018 and 2019. Our goal was to disseminate basic principles of coding in a fun and accessible way, reaching young children. In the activity, each participant was given a small set of 3D shapes - the...

MoCA is a bi-modal dataset in which we collect Motion Capture data and video sequences acquired from multiple views, including an ego-like viewpoint, of upper body actions in a cooking scenario. It has been collected with the specific purpose of investigating view-invariant action properties in both biological and artificial systems. Besides...

Understanding which features humans rely on-in visually recognizing action similarity is a crucial step towards a clearer picture of human action perception from a learning and developmental perspective. In the present work, we investigate to which extent a computational model based on kinematics can determine action similarity and how its...