arXiv subjects

Maurizio Porfiri

Publications and source records attributed to Maurizio Porfiri.

At least 19 recordsLinked to original sources

arXiv2026

Comparing the Emotional Impact of Thematic Versus Episodic Framing in Visualization Text

Although textual framing in data visualizations is known to influence comprehension, recall, and perceptions of bias, its effects on viewers' emotional responses remain underexplored. Drawing on two widely studied framing strategies in political communication, we examine how episodic framing (foregrounding a specific event) versus thematic framing (foregrounding broader trends) affects emotional and attitudinal responses to visualizations. We conducted a preregistered, between-subjects online experiment (N = 800) in which participants viewed identical visualizations of U.S. mass shooting data that varied only in textual framing: a thematic title, a thematic title with annotation, or an episodic title paired with the same annotation. Results show that episodic framing elicited significantly more negative emotional valence than both thematic conditions. In contrast, adding an annotation to a thematic title did not alter emotional impact. While framing did not significantly affect policy attitudes, mediation analysis revealed a significant indirect effect: increased negative emotion under episodic framing predicted greater support for gun control. These findings position emotion as a critical, yet underexamined, dimension of how textual framing shapes responses to data visualizations.

cs.HC↗

arXiv2026

Evaluating OCR Performance for Assistive Technology: Effects of Walking Speed, Camera Placement, and Camera Type

Optical character recognition (OCR), a process that converts printed or handwritten text into machine-readable form, is widely used in assistive technology for people with blindness and low vision. Yet most evaluations rely on static datasets that do not reflect the challenges of mobile use. In this study, we systematically evaluated OCR performance under both static and dynamic conditions. Static tests measured detection range across distances of 1-7 meters and viewing angles of 0-75 degrees horizontally. Dynamic tests examined the impact of motion by varying walking speed from slow (0.8 m/s) to very fast (1.8 m/s) and compared three camera mounting positions: head-mounted, shoulder-mounted, and handheld. We evaluated both a smartphone and smart glasses, using the phone's main and ultra-wide cameras. Four OCR engines were benchmarked to assess accuracy at different distances and viewing angles: Google Vision, PaddleOCR 3.0, EasyOCR, and Tesseract. PaddleOCR 3.0 was then used to evaluate OCR performance under dynamic walking conditions. Accuracy was computed at the character-level using the Levenshtein ratio against manually defined ground truth. Results showed that recognition accuracy declined with increased walking speed and wider viewing angles. Google Vision achieved the highest overall accuracy, with PaddleOCR close behind as the strongest open-source alternative. Across devices, the phone's main camera achieved the highest accuracy, and a shoulder-mounted placement yielded the highest average among body positions; however, differences among shoulder, head, and hand were not statistically significant.

cs.CV↗

arXiv2026

Studying the Separability of Visual Channel Pairs in Symbol Maps

Visualizations often encode multivariate data by mapping attributes to distinct visual channels such as color, size, or shape. The effectiveness of these encodings depends on separability--the extent to which channels can be perceived independently. Yet systematic evidence for separability, especially in map-based contexts, is lacking. We present a crowdsourced experiment that evaluates the separability of four channel pairs--color (ordered) x shape, color (ordered) x size, size x shape, and size x orientation--in the context of bivariate symbol maps. Both accuracy and speed analyses show that color x shape is the most separable and size x orientation the least separable, while size x color and size x shape do not differ. Separability also proved asymmetric--performance depended on which channel encoded the task-relevant variable, with color and shape outperforming size, and square shape especially difficult to discriminate. Our findings advance the empirical understanding of visual separability, with implications for multivariate map design.

cs.HC↗

arXiv2026

Bio-inspired density control of multi-agent swarms via leader-follower plasticity

The design of control systems for the spatial self-organization of mobile agents is an open challenge across several engineering domains, including swarm robotics and synthetic biology. Here, we propose a bio-inspired leader-follower solution, which is aware of energy constraints of mobile agents and is apt to deal with large swarms. Akin to many natural systems, control objectives are formulated for the entire collective, and leaders and followers are allowed to plastically switch their role in time. We frame a density control problem, modeling the agents' population via a system of nonlinear partial differential equations. This approach allows for a compact description that inherently avoids the curse of dimensionality and improves analytical tractability. We derive analytical guarantees for the existence of desired steady-state solutions and their local stability for one-dimensional and higher-dimensional problems. We numerically validate our control methodology, offering support to the effectiveness, robustness, and versatility of our proposed bio-inspired control strategy.

eess.SY↗

arXiv2026

Exploring the Use of VLMs for Navigation Assistance for People with Blindness and Low Vision

This paper investigates the potential of vision-language models (VLMs) to assist people with blindness and low vision (pBLV) in navigation tasks. We evaluate state-of-the-art closed-source models, including GPT-4V, GPT-4o, Gemini-1.5-Pro, and Claude-3.5-Sonnet, alongside open-source models, such as Llava-v1.6-mistral and Llava-onevision-qwen, to analyze their capabilities in foundational visual skills: counting ambient obstacles, relative spatial reasoning, and common-sense wayfinding-pertinent scene understanding. We further assess their performance in navigation scenarios, using pBLV-specific prompts designed to simulate real-world assistance tasks. Our findings reveal notable performance disparities between these models: GPT-4o consistently outperforms others across all tasks, particularly in spatial reasoning and scene understanding. In contrast, open-source models struggle with nuanced reasoning and adaptability in complex environments. Common challenges include difficulties in accurately counting objects in cluttered settings, biases in spatial reasoning, and a tendency to prioritize object details over spatial feedback, limiting their usability for pBLV in navigation tasks. Despite these limitations, VLMs show promise for wayfinding assistance when better aligned with human feedback and equipped with improved spatial reasoning. This research provides actionable insights into the strengths and limitations of current VLMs, guiding developers on effectively integrating VLMs into assistive technologies while addressing key limitations for enhanced usability.

cs.CV↗

arXiv2026

A Multimodal Assistive System for Product Localization and Retrieval for People who are Blind or have Low Vision

Shopping is a routine activity for sighted individuals, yet for people who are blind or have low vision (pBLV), locating and retrieving products in physical environments remains a challenge. This paper presents a multimodal wearable assistive system that integrates object detection with vision-language models to support independent product or item retrieval, with the goal of enhancing users'autonomy and sense of agency. The system operates through three phases: product search, which identifies target products using YOLO-World detection combined with embedding similarity and color histogram matching; product navigation, which provides spatialized sonification and VLM-generated verbal descriptions to guide users toward the target; and product correction, which verifies whether the user has reached the correct product and provides corrective feedback when necessary. Technical evaluation demonstrated promising performance across all modules, with product detection achieving near-perfect accuracy at close range and high accuracy when facing shelves within 1.5 m. VLM-based navigation achieved up to 94.4% accuracy, and correction accuracy exceeded 86% under optimal model configurations. These results demonstrate the system's potential to address the last-meter problem in assistive shopping. Future work will focus on user studies with pBLV participants and integration with multi-scale navigation ecosystems.

cs.HC↗

arXiv2025

Robust Computer-Vision based Construction Site Detection for Assistive-Technology Applications

Purpose: Navigating urban environments poses significant challenges for individuals who are blind or have low vision, especially in areas affected by construction. Construction zones introduce hazards such as uneven surfaces, barriers, hazardous materials, excessive noise, and altered routes that obstruct familiar paths and compromise safety. Although navigation tools assist in trip planning, they often overlook these temporary obstacles. Existing hazard detection systems also struggle with the visual variability of construction sites. Methods: We developed a computer vision--based assistive system integrating three modules: an open-vocabulary object detector to identify diverse construction-related elements, a YOLO-based model specialized in detecting scaffolding and poles, and an optical character recognition module to interpret construction signage. Results: In static testing at seven construction sites using images from multiple stationary viewpoints, the system achieved 88.56% overall accuracy. It consistently identified relevant objects within 2--10 meters and at approach angles up to 75$^{\circ}$. At 2--4 meters, detection was perfect (100%) across all angles. Even at 10 meters, six of seven sites remained detectable within a 15$^{\circ}$ approach. In dynamic testing along a 0.5-mile urban route containing eight construction sites, the system analyzed every frame of a first-person walking video. It achieved 87.26% accuracy in distinguishing construction from non-construction areas, rising to 92.0% with a 50-frame majority vote filter. Conclusion: The system can reliably detect construction sites in real time and at sufficient distances to provide advance warnings, enabling individuals with visual impairments to make safer mobility decisions such as proceeding with caution or rerouting.

cs.CV↗

arXiv2025

Seeing Identity in Data: Can Anthropographics Uncover Racial Homophily in Emotional Responses?

Racial homophily refers to the tendency of individuals to associate with others of the same racial or ethnic background. A recent study found no evidence of racial homophily in responses to mass shooting data visualizations. To increase the likelihood of detecting an effect, we redesigned the experiment by replacing bar charts with anthropographics and expanding the sample size. In a crowdsourced study (N=720), we showed participants a pictograph of mass shooting victims in the United States, with victims from one of three racial groups (Hispanic, Black, or White) highlighted. Each participant was assigned a visualization highlighting either their own racial group or a different racial group, allowing us to assess the influence of racial concordance on changes in affect (emotion). We found that, across all conditions, racial concordance had a modest but significant effect on changes in affect, with participants experiencing greater negative affect change when viewing visualizations highlighting their own race. This study provides initial evidence that racial homophily can emerge in responses to data visualizations, particularly when using anthropographics.

cs.HC↗

arXiv2025

Modeling Social Systems: Transparency, Reproducibility, and Responsibility

Mathematical models of complex social systems can enrich social scientific theory, inform interventions, and shape policy. From voting behavior to economic inequality and urban development, such models influence decisions that affect millions of lives. Thus, it is especially important to formulate and present them with transparency, reproducibility, and humility. Modeling in social domains, however, is often uniquely challenging. Unlike in physics or engineering, researchers often lack controlled experiments or abundant, clean data. Observational data is sparse, noisy, partial, and missing in systematic ways. In such an environment, how can we build models that can inform science and decision-making in transparent and responsible ways?

math.HO↗

arXiv2025

Leader-Follower Density Control of Spatial Dynamics in Large-Scale Multi-Agent Systems

We address the problem of controlling the density of a large ensemble of follower agents by acting on a group of leader agents that interact with them. Using coupled partial integro-differential equations to describe leader and follower density dynamics, we establish feasibility conditions and develop two control architectures ensuring global stability. The first employs feed-forward control on the followers' and a feedback on the leaders' density. The second implements a dual feedback loop through a reference-governor that adapts the leaders' density based on both populations' measurements. Our methods, initially developed in a one-dimensional setting, are extended to multi-dimensional cases, and validated through numerical simulations for representative control applications, both for groups of infinite and finite size.

eess.SY↗

arXiv2024

Predicting the role of inequalities on human mobility patterns

Whether in search of better trade opportunities or escaping wars, humans have always been on the move. For almost a century, mathematical models of human mobility have been instrumental in the quantification of commuting patterns and migratory fluxes. Equity is a common premise of most of these mathematical models, such that living conditions and job opportunities are assumed to be equivalent across cities. Growing inequalities in modern urban economy and pressing effects of climate change significantly strain this premise. Here, we propose a mobility model that is aware of inequalities across cities in terms of living conditions and job opportunities. Comparing results with real datasets, we show that the proposed model outperforms the state-of-the-art in predicting migration patterns in South Sudan and commuting fluxes in the United States. This model paves the way to critical research on resilience and sustainability of urban systems.

cond-mat.stat-mech↗

arXiv2024

Multi-faceted Sensory Substitution for Curb Alerting: A Pilot Investigation in Persons with Blindness and Low Vision

Curbs -- the edge of a raised sidewalk at the point where it meets a street -- crucial in urban environments where they help delineate safe pedestrian zones, from dangerous vehicular lanes. However, curbs themselves are significant navigation hazards, particularly for people who are blind or have low vision (pBLV). The challenges faced by pBLV in detecting and properly orientating themselves for these abrupt elevation changes can lead to falls and serious injuries. Despite recent advancements in assistive technologies, the detection and early warning of curbs remains a largely unsolved challenge. This paper aims to tackle this gap by introducing a novel, multi-faceted sensory substitution approach hosted on a smart wearable; the platform leverages an RGB camera and an embedded system to capture and segment curbs in real time and provide early warning and orientation information. The system utilizes YOLO (You Only Look Once) v8 segmentation model, trained on our custom curb dataset for the camera input. The output of the system consists of adaptive auditory beeps, abstract sonification, and speech, conveying information about the relative distance and orientation of curbs. Through human-subjects experimentation, we demonstrate the effectiveness of the system as compared to the white cane. Results show that our system can provide advanced warning through a larger safety window than the cane, while offering nearly identical curb orientation information.

cs.HC↗

arXiv2024

Haptics-based, higher-order Sensory Substitution designed for Object Negotiation in Blindness and Low Vision: Virtual Whiskers

People with blindness and low vision (pBLV) face challenges in navigating. Mobility aids are crucial for enhancing independence and safety. This paper presents an electronic travel aid that leverages a haptic-based, higher-order sensory substitution approach called Virtual Whiskers, designed to help pBLV negotiate obstacles effectively, efficiently, and safely. Virtual Whiskers is equipped with a plurality of modular vibration units that operate independently to deliver haptic feedback to users. Virtual Whiskers features two navigation modes: open path mode and depth mode, each addressing obstacle negotiation from different perspectives. The open path mode detects and delineate a traversable area within an analyzed field of view. Then, it guides the user through to the traversable direction adaptive vibratory feedback. The depth mode assists users in negotiating obstacles by highlighting spatial areas with prominent obstacles via haptic feedback. We recruited 10 participants with blindness or low vision to participate in user testing for Virtual Whiskers. Results show that the device significantly reduces idle periods and decreases the number of cane contacts. Virtual Whiskers is a promising obstacle negotiation strategy that demonstrating great potential to assist with pBLV navigation.

cs.HC↗

arXiv2024

Connections Beyond Data: Exploring Homophily With Visualizations

Homophily refers to the tendency of individuals to associate with others who are similar to them in characteristics, such as, race, ethnicity, age, gender, or interests. In this paper, we investigate if individuals exhibit racial homophily when viewing visualizations, using mass shooting data in the United States as the example topic. We conducted a crowdsourced experiment (N=450) where each participant was shown a visualization displaying the counts of mass shooting victims, highlighting the counts for one of three racial groups (White, Black, or Hispanic). Participants were assigned to view visualizations highlighting their own race or a different race to assess the influence of racial concordance on changes in affect (emotion) and attitude towards gun control. While we did not find evidence of homophily, the results showed a significant negative shift in affect across all visualization conditions. Notably, political ideology significantly impacted changes in affect, with more liberal views correlating with a more negative affect change. Our findings underscore the complexity of reactions to mass shooting visualizations and suggest that future research should consider various methodological improvements to better assess homophily effects.

cs.HC↗

arXiv2024

Mixed Reality Environment and High-Dimensional Continuification Control for Swarm Robotics

Many new methodologies for the control of large-scale multi-agent systems are based on macroscopic representations of the emerging system dynamics, in the form of continuum approximations of large ensembles. These techniques, that are developed in the limit case of an infinite number of agents, are usually validated only through numerical simulations. In this paper, we introduce a mixed reality set-up for testing swarm robotics techniques, focusing on the macroscopic collective motion of robotic swarms. This hybrid apparatus combines both real differential drive robots and virtual agents to create a heterogeneous swarm of tunable size. We also extend continuification-based control methods for swarms to higher dimensions, and assess experimentally their validity in the new platform. Our study demonstrates the effectiveness of the platform for conducting large-scale swarm robotics experiments, and it contributes new theoretical insights into control algorithms exploiting continuification approaches.

cs.RO↗

arXiv2024

High-dimensional continuification control of large-scale multi-agent systems under limited sensing and perturbations

This paper investigates the robustness of a novel high-dimensional continuification control method for complex multi-agent systems. We begin by formulating a partial differential equation describing the spatio-temporal density dynamics of swarming agents. A stable control action for the density is then derived and validated under nominal conditions. Subsequently, we discretize this macroscopic strategy into actionable velocity inputs for the system's agents. Our analysis demonstrates the robustness of the approach beyond idealized assumptions of unlimited sensing and absence of perturbations.

eess.SY↗

arXiv2023

Extreme flow simulations reveal skeletal adaptations of deep-sea sponges

Since its discovery, the deep-sea glass sponge Euplectella aspergillum has attracted interest in its mechanical properties and beauty. Its skeletal system is composed of amorphous hydrated silica and is arranged in a highly regular and hierarchical cylindrical lattice that begets exceptional flexibility and resilience to damage. Structural analyses dominate the literature, but hydrodynamic fields that surround and penetrate the sponge have remained largely unexplored. Here we address an unanswered question: whether, besides improving its mechanical properties, the skeletal motifs of E. aspergillum underlie the optimization of the flow physics within and beyond its body cavity. We use extreme flow simulations based on the 'lattice Boltzmann' method, featuring over fifty billion grid points and spanning four spatial decades. These in silico experiments reproduce the hydrodynamic conditions on the deep-sea floor where E. aspergillum lives. Our results indicate that the skeletal motifs reduce the overall hydrodynamic stress and support coherent internal recirculation patterns at low flow velocity. These patterns are arguably beneficial to the organism for selective filter feeding and sexual reproduction11,12. The present study reveals mechanisms of extraordinary adaptation to live in the abyss, paving the way towards further studies of this type at the intersection between fluid mechanics, organism biology and functional ecology.

physics.flu-dyn↗

arXiv2023

Continuification control of large-scale multiagent systems under limited sensing and structural perturbations

We investigate the stability and robustness properties of a continuification-based strategy for the control of large-scale multiagent systems. Within continuation-based strategy, one transforms the microscopic, agent-level description of the system dynamics into a macroscopic continuum-level, for which a control action can be synthesized to steer the macroscopic dynamics towards a desired distribution. Such an action is ultimately discretized to obtain a set of deployable control inputs for the agents to achieve the goal. The mathematical proof of convergence toward the desired distribution typically relies on the assumptions that no disturbance is present and that each agent possesses global knowledge of all the others' positions. Here, we analytically and numerically address the possibility of relaxing these assumptions for the case of a one-dimensional system of agents moving in a ring. We offer compelling evidence in favor of the use of a continuification-based strategy when agents only possess a finite sensing capability and spatio-temporal perturbations affect the macroscopic dynamics of the ensemble. We also discuss some preliminary results about the role of an integral action in the macroscopic control solution.

eess.SY↗