41 Result(s)
within
Conference Paper
Giovanni Maria Farinella
Computer Science
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Chapter and Conference Paper
The UNICT-TEAM Vision Modules for the Mohamed Bin Zayed International Robotics Challenge 2020
Real-world advanced robotics applications cannot be conceived without the employment of onboard visual perception. By perception we refer not only to image acquisition, but more importantly to the information ...
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Chapter and Conference Paper
MOVING: A MOdular and Flexible Platform for Embodied VIsual NaviGation
We present MOVING, a flexible and modular hardware and software platform for visual map** and navigation in the real world. The platform comprises a flexible sensor configuration consisting of an RGB-D camer...
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Chapter and Conference Paper
HERO: A Multi-modal Approach on Mobile Devices for Visual-Aware Conversational Assistance in Industrial Domains
We present HERO, an artificial assistant designed to communicate with users with both natural language and images to aid them carrying out procedures in industrial contexts. Our system is composed of five modu...
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Chapter and Conference Paper
Quasi-Online Detection of Take and Release Actions from Egocentric Videos
In this paper, we considered the problem of detecting object take and release actions from untrimmed egocentric videos in an industrial domain. Rather than requiring that actions are recognized as they are obs...
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Chapter and Conference Paper
SCENE-pathy: Capturing the Visual Selective Attention of People Towards Scene Elements
We present SCENE-pathy, a dataset and a set of baselines to study the visual selective attention (VSA) of people towards the 3D scene in which they are located. In practice, VSA allows to discover which parts of ...
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Chapter and Conference Paper
An Optimized Pipeline for Image-Based Localization in Museums from Egocentric Images
With the increasing interest in augmented and virtual reality, visual localization is acquiring a key role in many downstream applications requiring a real-time estimate of the user location only from visual s...
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Chapter and Conference Paper
Egocentric Human-Object Interaction Detection Exploiting Synthetic Data
We consider the problem of detecting Egocentric Human-Object Interactions (EHOIs) in industrial contexts. Since collecting and labeling large amounts of real images is challenging, we propose a pipeline and a ...
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Chapter and Conference Paper
Weakly Supervised Attended Object Detection Using Gaze Data as Annotations
We consider the problem of detecting and recognizing the objects observed by visitors (i.e., attended objects) in cultural sites from egocentric vision. A standard approach to the problem involves detecting al...
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Chapter and Conference Paper
Unsupervised Multi-camera Domain Adaptation for Object Detection in Cultural Sites
Domain adaptation approaches can be used to efficiently train object detectors by leveraging labeled synthetic images, inexpensively generated from 3D models, and unlabeled real images, which are cheaper to o...
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Chapter and Conference Paper
Panoptic Segmentation in Industrial Environments Using Synthetic and Real Data
Being able to understand the relations between the user and the surrounding environment is instrumental to assist users in a worksite. For instance, understanding which objects a user is interacting with from ...
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Chapter and Conference Paper
Untrimmed Action Anticipation
Egocentric action anticipation consists in predicting a future action the camera wearer will perform from egocentric video. While the task has recently attracted the attention of the research community, curren...
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Chapter and Conference Paper
Learning to Rank Food Images
In the last decade food understanding has become a very attractive topic. This has implied the growing demand of Computer Vision algorithms for automatic diet assessment to treat or prevent food related diseases
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Chapter and Conference Paper
Prediction of Social Image Popularity Dynamics
This paper introduces the new challenge of forecasting the engagement score reached by social images over time
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Chapter and Conference Paper
Leveraging Uncertainty to Rethink Loss Functions and Evaluation Measures for Egocentric Action Anticipation
Current action anticipation approaches often neglect the intrinsic uncertainty of future predictions when loss functions or evaluation measures are designed. The uncertainty of future observations is especiall...
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Chapter and Conference Paper
Scaling Egocentric Vision: The Dataset
First-person vision is gaining interest as it offers a unique viewpoint on people’s interaction with objects, their attention, and even intention. However, progress in this challenging domain has been relative...
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Chapter and Conference Paper
On the Estimation of Children’s Poses
Deep Learning architectures have obtained significant results for human pose estimation in the last years. Studies of the state of the art usually focus their attention on the estimation of the human pose of a...
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Chapter and Conference Paper
GRAPHJ: A Forensics Tool for Handwriting Analysis
Handwriting analysis is a standard forensics practice to assess the identity of a person from written documents. Forensic document examiners consider different features related to the motion and pressure of th...
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Chapter and Conference Paper
A System for Autonomous Landing of a UAV on a Moving Vehicle
This paper describes the approach employed to implement the autonomous landing of an Unmanned Aerial Vehicle (UAV) upon a moving ground vehicle. We consider an application scenario in which a target, made of a...
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Chapter and Conference Paper
A Multimedia Database for Automatic Meal Assessment Systems
A healthy diet is crucial for maintaining overall health and for controlling food-related chronic diseases, like diabetes and obesity. Proper diet management however, relies on the rather challenging task of ...
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Chapter and Conference Paper
Recognizing Context for Privacy Preserving of First Person Vision Image Sequences
The constant increasing evolution of life-logging wearable devices, as well as the fast grow of their market, has introduced relevant changes in the acquisition, storage and automatic understanding of images a...
