This study provides researchers, who are considering internet-based social cognitive research, with a general overview of the theoretical and methodological considerations that must be considered for implementing best practices. It covers theoretical discussions of the ways in which the internet has affected socialisation and cognitive processes (including memory and attention), the balance between ecological validity and experimental control for internet-based social cognitive research (including the effect of digital researcher presence), and group membership (including discussions of group composition, identity misrepresentation, and communication through memes). It also covers methodological discussions and best practices to account for the effects of internet use on social cognition, exploring avenues for increasing experimental control without sacrificing ecological validity, and decisions pertaining to participant recruitment issues, when recruiting from internet-based community groups.
Naturalness is a complex appearance attribute that is dependent on multiple visual appearance attributes like color, gloss, roughness, and their interaction. It impacts the perceived quality of an object and should therefore be reproduced correctly. In recent years, the use of color 3D printing technology has seen considerable growth in different fields like cultural heritage, medical, entertainment, and fashion for producing 3D objects with the correct appearance. This paper investigates the reproduction of naturalness attribute using a color 3D printing technology and the naturalness perception of the 3D printed objects. Results indicate that naturalness perception of 3D printed objects is highly subjective but is found to be objectively dependent mainly on a printed object’s surface elevation and roughness.
Evaluating perceptual image and video quality is crucial for multimedia technology development. This study investigated nation-based differences in quality assessment using three large-scale crowdsourced datasets (KonIQ-10k, KADID-10k, NIVD), analyzing responses from diverse countries including the US, Japan, India, Brazil, Venezuela, Russia, and Serbia. We hypothesized that cultural factors influence how observers interpret and apply rating scales like the Absolute Category Rating (ACR) and Degradation Category Rating (DCR). Our advanced statistical models, employing both frequentist and Bayesian approaches, incorporated country-specific components such as variable thresholds for rating categories and lapse rates to account for unintended errors. Our analysis revealed significant cross-cultural variations in rating behavior, particularly regarding extreme response styles. Notably, US observers showed a 35–39% higher propensity for extreme ratings compared to Japanese observers when evaluating the same video stimuli, aligning with established research on cultural differences in response styles. Furthermore, we identified distinct patterns in threshold placement for rating categories across nationalities, indicating culturally influenced variations in scale interpretation. These findings contribute to a more comprehensive understanding of image quality in a global context and have important implications for quality assessment dataset design, offering new opportunities to investigate cultural differences difficult to capture in laboratory environments.
Routing through a dynamic environment is mostly carried out by using maps that integrate information about time-dependent parameters, such as traffic conditions and spatial constraints, which is a challenging and cumbersome task. We address the complex scenario where a user has to plan a route on a network that is dynamic with respect to edges that change their congestion through time. We perform an experimental user study where we compare interactive and non-interactive interfaces, the complexity levels of the map structures (number of nodes and edges) and of the paths (number of nodes that need to be visited), and the effects of familiarity with the map. The results of our study indicate that an interactive interface is more beneficial than a non-interactive interface for more complex paths, while a non-interactive interface is more beneficial than an interactive interface for less complex paths. In detail, while the number of nodes and edges of the network had no effect on the performance, we observed that (not surprisingly) the more complex the path, the longer the processing time and the lower the correctness. We tested the familiarity with a test–retest design, where we organized a second session of tests, labeled T2, after the first session T1. We observed a familiarization effect in T2, that is, the participants’ performance improved for the networks known from T1.
In recent years, the effects of light pollution have become significant, and the need for image reproduction of a faithful and preferred starry sky has increased. Previous studies have analyzed the relationships between the luminance, size, and color temperature of stars and the fidelity and nature of their appearance, as well as color perception. This study examines the depth perception of stars. We consider starry sky images as a set of “small-field light sources” that can be viewed as point light sources with minimal viewing angles. Our goal was to experimentally elucidate the cues for depth perception. In our experiments, observers viewed two points of different sizes, luminances, and color temperatures and selected the one perceived to be in front to confirm the relationship between the three depth cues of retinal image; size, light attenuation, and color, and their association with depth perception. Results confirmed that retinal image size and light attenuation were relevant for a small-field light source. Results also suggest that the interaction between retinal image size and light attenuation may be explained by retinal illuminance. However, the effect of color was small, and the point with higher saturation was more likely to be perceived in front, when the hue was close to that of the point.
This article examines the influence of facial features on the perception and evaluation of avatars in virtual environments. As people increasingly engage with avatars in virtual spaces, the visual appearance of these digital representations is critical to the design of human-computer interaction. Drawing on research on the evaluation of human faces, this study investigates how facial features influence perceptions of an avatar’s attractiveness, trustworthiness, personality traits, and other characteristics. We conducted two factorial experiments that manipulated the avatars’ eye size, jaw shape, and hairstyle. It was found that larger eyes conveyed a more positive impression and increased perceptions of attractiveness, sympathy, trustworthiness, extraversion, and openness. Although avatars with prominent jawlines were rated as more attractive, a prominent jawline was associated with a perception of higher dominance and threat. Stylish hairstyles were associated with higher extraversion and openness but also with lower conscientiousness. This study provides important insights into the design of avatars for virtual applications like gaming, e-commerce, and online therapy. It highlights the complex interplay between facial features and perception and contributes to the knowledge of how avatars can be optimally designed to create the desired impressions in virtual environments.
In recent years, the need for replication efforts has grown. Replication science faces key challenges, including achieving generalizability across heterogeneous samples and environments while streamlining the theory-experiment cycle to facilitate research efforts. Systematic replication projects using Internet-based methodologies address these challenges by facilitating access to diverse samples, employing rigorous testing, reducing costs, and ensuring materials are readily available. Standards for Internet-based experimenting provides transparency and reproducibility. We present three remote experiments, including one exact replication (N: 410) and two conceptual replications (N: 270; N: 365), which test the mental accounting effect based on Kahneman and Tversky’s classic paradigm. The remote version of the exact replication maintained the same experimental design, instructions, and procedure as the original paradigm. In the two conceptual replications, we adapted the original price to the current value of money: Ticket price and the monetary loss were changed from 10$ to 40€. In the first conceptual replication, we varied the original experimental design: the mental account variable was manipulated within-subjects. In the second conceptual replication, we varied the price stimulus while retaining the mental account manipulation in a between-subjects design. The exact replication replicated the original findings with an effect of small size, while the two conceptual replications replicated the results with an effect of increased size that is more comparable to the original findings. The results highlight the importance of adapting experimental paradigms to the current times, and the advantages of conducting remote replication projects step-by-step.
Augmented reality (AR) combines elements of the real world with additional virtual content, creating a blended viewing environment. Optical see-through AR (OST-AR) accomplishes this by using a transparent beam splitter to overlay virtual elements over a user’s view of the real world. However, the inherent see-through nature of OST-AR carries challenges for color appearance, especially around the appearance of darker and less chromatic objects. When displaying human faces—a promising application of AR technology—these challenges disproportionately affect darker skin tones, making them appear more transparent than lighter skin tones. Still, some transparency in the rendered object may not be entirely negative; people’s evaluations of transparency when interacting with other humans in AR-mediated modalities are not yet fully understood. In this work, two psychophysical experiments were conducted to assess how people evaluate OST-AR transparency across several characteristics including different skin tones, object types, lighting conditions, and display types. The results provide a scale of perceived transparency allowing comparisons to transparency for conventional emissive displays. The results also demonstrate how AR transparency impacts perceptions of object preference and fit within the environment. These results reveal several areas with need for further attention, particularly regarding darker skin tones, lighter ambient lighting, and displaying human faces more generally. This work may be useful in guiding the development of OST-AR technology, and emphasizes the importance of AR design goals, perception of human faces, and optimizing visual appearance in extended reality systems.
The area of uncertainty visualization attempts to determine the impact of alternative representations and evaluate their effectiveness in decision-making. Uncertainties are often an integral part of data, and model predictions often contain a significant amount of uncertain information. In this study, we explore a novel idea for a visualization to present data uncertainty using simulated chromatic aberration (CA). To produce uncertain data to visualize, we first utilized existing machine learning models to generate predictive results using public health data. We then visualize the data itself and the associated uncertainties with artificially spatially separated color channels, and the user perception of this CA representation is evaluated in a comparative user study. From quantitative analysis, it is observed that users are able to identify targets with the CA method more accurately than the comparator state-of-the-art approach. In addition, the speed of target identification was significantly faster in CA as compared to the alternative, but the subjective preferences of users do not vary significantly between the two.
Individuals with aphantasia report either absent or dramatically reduced mental imagery compared to control participants. The image of an object or scene produced “in the mind’s eye” lacks detail for these individuals or is simply not there. Line drawings made from memory are a straightforward way to assess the contents of visual imagery for aphantasic individuals relative to controls. Prior analyses of the Aphantasia Drawing Database have revealed specific impairments in visual memory for objects, but relatively spared scene accuracy, suggesting that the encoding of visual scenes in aphantasia is more complex than an overall reduction in imagery might suggest. Here, we examined the mid-level image statistics of line drawings from this database to determine how simpler visual feature distributions differed as a function of aphantasia and reliance on image recall rather than direct observation during image reproduction. We find clear differences across several different sets of mid-level properties as a function of aphantasia, which offers further characterization of the nature of visual encoding in this condition.