Search Results (5)

This paper identifies the various influences of Western aesthetic preferences of landscapes in answer to the question, why do humans find landscapes attractive? A four-level model of influences is proposed, based on the innate or evolutionary influences applicable to all humanity, through the cultural and the societal to the individual. At each level there are a number of contributory factors at play, and these are described. The paper is confined to Western perspectives of landscape aesthetics. At the innate level are four landscape theories that postulate the reasons why humans find landscapes attractive. Also at the innate level are the philosophical underpinnings of human delight in landscapes and the Gestalt influence on preferences. The cultural influence comprises the legend of Arcadia and the Golden Age; of classicism, teleology, and landscape painting; and the emergence of the sublime, the beautiful, the picturesque, and Romanticism. At the societal level are the artistic pursuits of landscape painting and the development of parks and gardens, which reflected the perfect Italianate landscape. Also at this level are Western society’s attitude to mountains, which changed radically in the seventeenth century. Individuals are influenced by psychoanalytical pressures on the subconscious, by unconscious experiences in infancy such as a human’s preference for water, and by the influence of neuroaesthetics, which describes how the areas of the brain respond to aesthetic objects. Finally, research of landscape preferences over 50 years provides insights on the influence of landscape components, reflecting the influence of the innate, cultural, and societal factors. The combined realms of influence of each of these factors are hypothesized to explain human responses to landscapes. Full article

Our eyes convey information about a person. The pupils may provide information regarding our emotional states when presented along with different emotional expressions. We examined the effects of pupil size and vergence on inferring other people’s characteristics in neutral expression eyes. Pupil sizes were manipulated by overlaying black disks onto the pupils of the original eye images. The disk area was then changed to create small, medium, and large pupils. Vergence was simulated by shifting the medium-sized disks nasally in one eye. Pupil sizes were exaggerated for Experiment 1 and followed values from the literature for Experiment 2. The first Purkinje image from the eye photos in Experiment 2 was kept to preserve image realism. The characteristics measured were sex, age, attractiveness, trustworthiness, intelligence, valence, and arousal. Participants completed one of two online experiments and rated eight eye pictures with differently sized pupils and with vergence eyes. Both experiments were identical except for the stimuli designs. Results from Experiment 1 revealed rating differences between pupil sizes for all characteristics except sex, age, and arousal. Specifically, eyes with extremely small pupil sizes and artificial vergence received the lowest ratings compared to medium and large pupil sizes. Results from Experiment 2 only indicated weak effects of pupil size and vergence, particularly for intelligence ratings. We conclude that the pupils can influence how characteristics of another person are perceived and may be regarded as important social signals in subconscious social interaction processes. However, the effects may be rather small for neutral expressions. Full article

In the current era of a strongly competitive business environment, it is more difficult for companies to attract customers. Consumer neuroscience has growing potential here, as it reveals internal consumer preferences by using innovative methods and tools, which can effectively examine consumer behavior and attract new customers. In particular, smell has a great ability to subconsciously influence customers and, thus, support profitability. This paper examines the importance of consumer neuroscience and its modern technologies used for exploring human perceptions to influence customers and benefit from the aromatization of business spaces. We focused our analysis on various service sectors. Despite the potential of the examined issue, there are a limited number of studies in the field of service providers that use neuroscience tools to examine the effect of aromas on human emotions. Most studies took place in laboratory conditions, and the used methodological procedures varied widely. Our analysis showed that, in spite of the positive impact of aromatization in the majority of aromatized spaces, service companies still do not use the potential of consumer neuroscience and aroma marketing to a sufficient degree. Innovative methods and tools, in particular, are still very underused. Full article

Eye-tracking technology is a biometric tool that has found many commercial and research applications. The recent advent of affordable wearable sensors has considerably expanded the range of these possibilities to fields such as computer gaming, education, entertainment, health, neuromarketing, psychology, etc. The Visual Attention Software by 3M (3M-VAS) is an artificial intelligence application that was formulated using experimental data from eye-tracking. It can be used to predict viewer reactions to images, generating fixation point probability maps and fixation point sequence estimations, thus revealing pre-attentive processing of visual stimuli with a very high degree of accuracy. We have used 3M-VAS software in an innovative implementation to analyze images of different buildings, either in their original state or photographically manipulated, as well as various geometric patterns. The software not only reveals non-obvious fixation points, but also overall relative design coherence, a key element of Christopher Alexander’s theory of geometrical order. A more evenly distributed field of attention seen in some structures contrasts with other buildings being ignored, those showing instead unconnected points of splintered attention. Our findings are non-intuitive and surprising. We link these results to both Alexander’s theory and Neuroscience, identify potential pitfalls in the software’s use, and also suggest ways to avoid them. Full article

Micro expressions are usually subtle and brief facial expressions that humans use to hide their true emotional states. In recent years, micro-expression recognition has attracted wide attention in the fields of psychology, mass media, and computer vision. The shortest micro expression lasts only 1/25 s. Furthermore, different from macro-expressions, micro-expressions have considerable low intensity and inadequate contraction of the facial muscles. Based on these characteristics, automatic micro-expression detection and recognition are great challenges in the field of computer vision. In this paper, we propose a novel automatic facial expression recognition framework based on necessary morphological patches (NMPs) to better detect and identify micro expressions. Micro expression is a subconscious facial muscle response. It is not controlled by the rational thought of the brain. Therefore, it calls on a few facial muscles and has local properties. NMPs are the facial regions that must be involved when a micro expression occurs. NMPs were screened based on weighting the facial active patches instead of the holistic utilization of the entire facial area. Firstly, we manually define the active facial patches according to the facial landmark coordinates and the facial action coding system (FACS). Secondly, we use a LBP-TOP descriptor to extract features in these patches and the Entropy-Weight method to select NMP. Finally, we obtain the weighted LBP-TOP features of these NMP. We test on two recent publicly available datasets: CASME II and SMIC database that provided sufficient samples. Compared with many recent state-of-the-art approaches, our method achieves more promising recognition results. Full article