Food appearance sets intentions and expectations. When designing packaged food much attention is devoted to packaging elements like color and shape, but less to the characteristics of the images used. To our awareness, no study has yet investigated how the appearance of the food shown on the package affects consumers’ preferences. Often, orange juice packages depict an orange. Juiciness being one of the most important parameters to assess oranges’ quality, we hypothesized that an orange with a juicier appearance on the package would improve the overall evaluation of the juice. Using image cues found to trigger juiciness perception of oranges depicted in 17th century paintings, we designed four orange juice packages by manipulating the highlights on the pulp (present vs. absent) and the state of the orange (unpeeled vs. peeled). In an online experiment, 400 participants, each assigned to one condition, rated expected naturalness, healthiness, quality, sweetness and tastiness of the juice, package attractiveness and willingness to buy. Finally, they rated juiciness of the orange for all four images. A one-way ANOVA showed a significant effect of the highlights on juiciness. A MANOVA showed that the presence of highlights, both in isolation and in interaction with the peeled side, also significantly increased expected quality and tastiness of the juice. The present study shows the importance of material perception and food texture appearance in the imagery of food packaging. We suggest that knowledge from vision science on image features and material perception should be integrated into the process of packaging design.@en

Painters mastered replicating the regularities of the visual patterns that we use to infer different materials and their properties, via meticulous observation of the way light reveals the world's textures. The convincing depiction of bunches of grapes is particularly interesting. A convincing portrayal of grapes requires a balanced combination of different material properties, such as glossiness, translucency and bloom, as we learn from the 17th-century pictorial recipe by Willem Beurs. These material properties, together with three-dimensionality and convincingness, were rated in experiment 1 on 17th-century paintings, and in experiment 2 on optical mixtures of layers derived from a reconstruction of one of the 17th-century paintings, made following Beurs's recipe. In experiment 3 only convincingness was rated, using again the 17th-century paintings. With a multiple linear regression, we found glossiness, translucency and bloom not to be good predictors of convincingness of the 17thcentury paintings, but they were for the reconstruction. Overall, convincingness was judged consistently, showing that people agreed on its meaning. However, the agreement was higher when the material properties indicated by Beurs were also rated (experiment 1) than if not (experiment 3), suggesting that these properties are associated with what makes grapes look convincing. The 17thcentury workshop practices showed more variability than standardization of grapes, as different combinations of the material properties could lead to a highly convincing representation. Beurs's recipe provides a list of all the possible optical interactions of grapes, and the economic yet effective image cues to render them. @en

Dutch 17th century painters were masters in depicting materials and their properties in a convincing way. Here, we studied the perception of the material signatures and key image features of different depicted fabrics, like satin and velvet. We also tested whether the perception of fabrics depicted in paintings related to local or global cues, by cropping the stimuli. In Experiment 1, roughness, warmth, softness, heaviness, hairiness, and shininess were rated for the stimuli shown either full figure or cropped. In the full figure, all attributes except shininess were rated higher for velvet, whereas shininess was rated higher for satin. This distinction was less clear in the cropped condition, and some properties were perceived significantly different between the two conditions. In Experiment 2 we tested whether this difference was due to the choice of the cropped area. On the basis of the results of Experiment 1, shininess and softness were rated for multiple crops from each fabric. Most crops from the same fabric differed significantly in shininess, but not in softness perception. Perceived shininess correlated positively with the mean luminance of the crops and the highlights’ coverage. Experiment 1 showed that painted velvet and satin triggered distinct perceptions, indicative of robust material signatures of the two fabrics. The results of Experiment 2 suggest that the presence of local image cues affects the perception of optical properties like shininess, but not mechanical properties such as softness.@en

Citrus fruits are characterized by a juicy and translucent interior, important properties that drive material recognition and food acceptance. Yet, a thorough understanding of their visual perception is still missing. Using citrus fruits depicted in 17th-century paintings as stimuli, we ran three rating experiments. In Experiment 1, participants rated the perceived similarity in translucency or juiciness of the fruits. In Experiment 2, different groups of participants rated one image feature from a list obtained in a preliminary experiment. In Experiment 3, translucency and juiciness were rated. We constructed two-dimensional perceptual spaces for both material properties and fitted the ratings of the image features into the spaces to interpret them. "Highlights," "peeled side," "bumpiness," and "color saturation" fit the juiciness space best and were high for the highly juicy stimuli. "Peeled side," "intensity of light gradient," "highlights," and "color saturation" were the most salient features of the translucency space, being high for the highly translucent stimuli. The same image features were also indicated in a 17th-century painting manual for material depiction (Beurs, 1692; Beurs, in press). Altogether, we disclosed the expertise of painters with regard to material perception by identifying the image features that trigger a visual impression of juiciness and translucency in citrus fruits.@en

Dutch Golden Age painters could convincingly depict all sorts of materials. How did they do it and how do we perceive them as such, are questions that only recently have started to be addressed by art historians and vision scientists, respectively. This paper aims to discuss how a booklet of pictorial recipes written by the Dutch painter Willem Beurs in 1692 constitutes an index of key image features for material depiction and perception. Beurs' recipes connect different materials according to their shared visual features, and offer the profiles, i.e., the optimal combinations, of these features to render a wide range of materials. By combining representation and perception, the knowledge of painters about the depiction of materials can help to understand the mechanisms of the visual system for material perception, and these in turn can explain the pictorial features that make the pictorial representation of materials so convincing. Keywords @en

This thesis explores convincing stuff depicted in 17th century paintings, with the primary aim of understanding their visual perception. ”Stuff” is the term first introduced by Edward Adelson in 2001 to differentiate materials from objects, and to call attention on the research gap in material perception. In an interesting parallel, the representation of materials in paintings constitutes a knowledge gap in art history as well. Both gaps have only recently been recognized and started to be addressed in their respective research fields. In this thesis, representation and perception come together to create a virtuous circle in which the knowledge of painters about the representation of materials is used to understand the mechanisms of the visual system for material perception, and this is in turn used to explain the pictorial features that make the representation of materials so convincing. The common thread used here to connect representation and perception, is ”The big world painted small”, a long-forgotten booklet of pictorial recipes written by the Dutch painter Willem Beurs in 1692. We argue that this book represents an index of key features for material perception, that means an index of image features that always work as perceptual cues regardless of the illumination and the viewing conditions of the depicted scene. The main research objective of this dissertation is: To understand the convincing depiction and perception of materials in 17th century paintings, connecting the image features found in paintings and listed by Beurs to their role as perceptual cues. In order to achieve this objective, we employed a novel, interdisciplinary research approach, merging science of human and computer vision, technical art history, and the historical textual source of Beurs. @en

To understand the key image features that we use to infer the glossiness of materials, we analyzed the pictorial shortcuts used by 17th century painters to imitate the optical phenomenon of specular reflections when depicting grapes. Gloss perception of painted grapes was determined via a rating experiment. We computed the contrast, blurriness, and coverage of the grapes' highlights in the paintings' images, inspired by Marlow and Anderson (2013). The highlights were manually segmented from the images, and next the features contrast, coverage, and blurriness were semiautomatically quantified using self-defined algorithms. Multiple linear regressions of contrast and blurriness resulted in a predictive model that could explain 69% of the variance in gloss perception. No effect was found for coverage. These findings are in agreement with the instructions to render glossiness of grapes contained in a 17th century painting manual (Beurs, 1692/in press), suggesting that painting practice embeds knowledge about key image features that trigger specific material percepts.@en

Intensive observation of the world, and the intention of realistically transferring it to the canvas, allowed Dutch Golden Age painters to develop an implicit knowledge of the visual patterns people use to infer different materials, imitating key optical phenomena via shortcuts. To understand the origin of the astonishing realism of Dutch 17th century paintings, we refer to the treatise of Willem Beurs, "The Big World Painted Small", a precious source of technical information about oil painting. One of the questions we aim to answer is: how did they produce such true-to-life depictions? We chose the representation of grapes as case study, due to the simultaneous presence and interaction of different material properties, like glossiness, translucency and bloom. Glossiness and translucency are of primary importance in vision science. Thus, understanding their rendering and perception for the case of grapes, can lay the groundwork for a more general theory of gloss and translucency. We investigated if the material properties proposed by Beurs to paint grapes are actually perceived in paintings, and how they relate to their perceived convincingness. Among these material qualities, we took a closer look at glossiness and tried to predict its perception via image statistics of specular reflections. @en

To unveil the mystery of the exquisitely rendered materials in Dutch 17 th century paintings, we need to understand the pictorial procedures of this period. We focused on the Dutch master Jan de Heem, known for his highly convincing still-lifes. We reconstructed his systematic multi-layered approach to paint grapes, based on pigment distribution maps, layers stratigraphy, and a 17 th century textual source. We digitised the layers reconstruction to access the temporal information of the painting procedure. We combined the layers via optical mixing into a digital tool that can be used to answer “what if” art historical questions about the painting composition, by editing the order, weight and colour of the layers. @en

To unveil the mystery of the exquisitely rendered materials in Dutch 17 th century paintings, we need to understand the pictorial procedures of this period. We focused on the Dutch master Jan de Heem, known for his highly convincing still-lifes. We reconstructed his systematic multi-layered approach to paint grapes, based on pigment distribution maps, layers stratigraphy, and a 17 th century textual source. We digitised the layers reconstruction to access the temporal information of the painting procedure. We combined the layers via optical mixing into a digital tool that can be used to answer “what if” art historical questions about the painting composition, by editing the order, weight and colour of the layers. @en

To unveil the mystery of the exquisitely rendered materials in Dutch 17 th century paintings, we need to understand the pictorial procedures of this period. We focused on the Dutch master Jan de Heem, known for his highly convincing still-lifes. We reconstructed his systematic multi-layered approach to paint grapes, based on pigment distribution maps, layers stratigraphy, and a 17 th century textual source. We digitised the layers reconstruction to access the temporal information of the painting procedure. We combined the layers via optical mixing into a digital tool that can be used to answer “what if” art historical questions about the painting composition, by editing the order, weight and colour of the layers. @en

To unveil the mystery of the exquisitely rendered materials in Dutch 17 th century paintings, we need to understand the pictorial procedures of this period. We focused on the Dutch master Jan de Heem, known for his highly convincing still-lifes. We reconstructed his systematic multi-layered approach to paint grapes, based on pigment distribution maps, layers stratigraphy, and a 17 th century textual source. We digitised the layers reconstruction to access the temporal information of the painting procedure. We combined the layers via optical mixing into a digital tool that can be used to answer “what if” art historical questions about the painting composition, by editing the order, weight and colour of the layers. @en