Effects of Appearance in Visual Palatability of Dishes for the Elderly under Several Lighting Conditions

This study aims to clarify the effect of the appearance of dishes on the visual palatability for elderly people concerning its color appearance, glossiness, and visual texture. We conducted a subjective experiment on visual palatability of dishes under different light sources. We used the digital images of 12 kinds of food dishes to give the subject the same visual stimuli with no olfactory cues. As a result, we found that elderly's "visual palatability" was affected by not only the "color appearance" but also the "glossiness" of dishes. This record was migrated from the OpenDepot repository service in June, 2017 before shutting down

Salsa dataset: primera base de conocimiento de música salsa

Salsa is a well-known musical genre and part of our cultural identity. Its origins date back to the 30s of the last century and it has grown in popularity since its origins. Ever since, by different artists in different regions of the world have modified the genre, through different visions of what salsa is, experimenting and adding new instruments and technology. Thus, salsa becomes an intrinsically complex and difficult genre in qualitative terms. However, little we know at a computational level, about which are the acoustic characteristics defining this music, to make it different from the rest of musical genres. In this paper we show the results of a process that builds a knowledge base of salsa music freely available to the scientific community. This base gathers acoustic information of over 20.000 salsa songs. We pretend to use this information to model different characteristics of the genre by means of AI techniques. In addition to making information accessible to researchers interested in salsa music, another important contribution of this project is to provide tools to enlarge the knowledge base with the help of the scientific community. To achieve this, we developed a software that extracts the pertinent acoustic information from songs belonging to users and then it includes them into the knowledge base.Un género musical muy conocido en nuestra región y que hace parte de nuestra identidad cultural caleña es la salsa. Su origen se remonta a los años 30 del siglo pasado y desde entonces este género ha sido modificado por diferentes artistas en diversas regiones del mundo, cada uno con una visión diferente de él, con experiencias culturales y con aporte de nuevos instrumentos y nueva tecnología. Esto hace que la salsa sea un género intrínsecamente complejo y difícil de definir en términos cualitativos. A pesar de la creciente popularidad del género en el mundo, la salsa no ha sido analizada desde el punto de vista computacional para derivar cuáles son los componentes acústicos que la definen y diferencian de los demás géneros musicales. En este documento abordaremos los resultados del proceso de creación de una base de conocimiento de música salsa que está disponible en forma gratuita para la comunidad científica y que recopila la información acústica de más de 20.000 canciones de dicho género musical. Con esta información, que caracteriza la señal acústica, se pretende modelar diferentes características del género mediante técnicas de inteligencia artificial. Además de hacer accesible esta información a investigadores interesados en la música salsa, otro aporte importante de este proyecto es proporcionar herramientas para que la base de conocimiento crezca con la ayuda de la comunidad científica. Para ello se desarrolló un software que extrae la información acústica pertinente de canciones que tienen los usuarios para ser enviada y adicionada a la base de conocimiento

Salsa dataset: primera base de conocimiento de música salsa

A well-known musical genre in our region and that is part of our cultural identity Caleña is salsa. Its origin dates back to the 30s of the last century and since then this genre has been modified by different artists in different regions of the world, each with a different vision of it, with cultural experiences and with the contribution of new instruments and new technology. This makes salsa an intrinsically complex genre and difficult to define in qualitative terms. Despite the growing popularity of the genre in the world, salsa has not been analyzed from the computational point of view to derive what are the acoustic components that define and differentiate it from other musical genres. In this document we will discuss the results of the process of creating a knowledge base of salsa music that is freely available to the scientific community and that collects the acoustic information of more than 20,000 songs of that musical genre. With this information, which characterizes the acoustic signal, it is intended to model different characteristics of the genre through artificial intelligence techniques. In addition to making this information accessible to researchers interested in salsa music, another important contribution of this project is to provide tools for the knowledge base to grow with the help of the scientific community. For this, a software was developed that extracts the pertinent acoustic information of songs that users have to be sent and added to the knowledge base.Un género musical muy conocido en nuestra región y que hace parte de nuestra identidad cultural caleña es la salsa. Su origen se remonta a los años 30 del siglo pasado y desde entonces este género ha sido modificado por diferentes artistas en diversas regiones del mundo, cada uno con una visión diferente de él, con experiencias culturales y con aporte de nuevos instrumentos y nueva tecnología. Esto hace que la salsa sea un género intrínsecamente complejo y difícil de definir en términos cualitativos. A pesar de la creciente popularidad del género en el mundo, la salsa no ha sido analizada desde el punto de vista computacional para derivar cuáles son los componentes acústicos que la definen y diferencian de los demás géneros musicales. En este documento abordaremos los resultados del proceso de creación de una base de conocimiento de música salsa que está disponible en forma gratuita para la comunidad científica y que recopila la información acústica de más de 20.000 canciones de dicho género musical. Con esta información, que caracteriza la señal acústica, se pretende modelar diferentes características del género mediante técnicas de inteligencia artificial. Además de hacer accesible esta información a investigadores interesados en la música salsa, otro aporte importante de este proyecto es proporcionar herramientas para que la base de conocimiento crezca con la ayuda de la comunidad científica. Para ello se desarrolló un software que extrae la información acústica pertinente de canciones que tienen los usuarios para ser enviada y adicionada a la base de conocimiento

Image information influencing the online purchase intention of vegetables products

La información visual de los productos ofrecidos a través de medios virtuales juega un papel importante en la intención de compra de los consumidores. En el caso de los productos perecederos, especialmente en los vegetales, dicha información cobra mayor relevancia, pues involucra aspectos sensoriales que los consumidores utilizan para decidir la compra. El objetivo principal del presente estudio es identificar y caracterizar el tipo de información visual necesaria para afectar la intención de compra de vegetales por medios virtuales y dimensionar los requerimientos técnicos y financieros que una organización del sector retail debe poner en consideración para presentar dicha información mediante el uso de tecnologías de información. Se abordan, además, otros factores que afectan la intención de compra online, los que, si bien no guardan relación con la presentación visual de los productos, están ligados a aspectos que deben ser considerados por las organizaciones para que todo el proceso de compra a través de medios virtuales sea satisfactorio para el cliente.Visual information of the products offered by virtual channels has an important role in the customer purchase intention, for the case of perishable products, especially for vegetables, such information becomes more important since it involves one of the sensory aspects that consumers use to decide whether or not to purchase. The principal goal of this study is to identify and characterize different types of visual information that affect vegetable purchase intention through virtual channels and determining the technical and financial requirements that a retail company should consider to present this information using information technologies. Other factors that also affect online purchase intention are included, and although unrelated to the products visual presentation, are tied to issues to be considered by organizations, so that the whole virtual buying process is satisfactory to the client

Model of vegetable freshness perception using luminance cues

Freshness perception is a quality discrimination process that influences our consumer choice and eating behavior, especially of highly perishable products such as vegetables. Previous research used photographic stimuli to investigate the relationship between luminance distribution and freshness perception for a cabbage leaf (C. Arce-Lopera, Masuda, Kimura, et al., 2013) and a strawberry (Carlos Arce-Lopera, Masuda, Kimura, Wada, & Okajima, 2012). In this study, the luminance and chromatic information of the freshness degradation process of four different vegetables (cabbage, strawberry, carrot and spinach) was recorded in a temperature, humidity and light controlled environment. However, instead of a camera, a 2D luminance and chromaticity analyzer (TOPCON UA1000) was chosen as the measurement equipment. Then, using a color management system to guarantee the exact reproduction of the recorded luminance and chromatic data of the real objects, a color and a grayscale version of the stimuli was created. Subsequently, those pictures were randomly presented to subjects who had to rate their perceived freshness using a visual analog scale. The achromatic results did not differ from the chromatic ones suggesting that luminance information is sufficient to enable an accurate estimation of vegetable freshness. Additionally, the original images were digitally manipulated only by modifying their luminance distribution and keeping their color information intact. When the resulting images were presented, using the same psychophysical experimental setting, the results showed that the perceived freshness also changed concordantly with the changes on the asymmetry of the luminance distribution. Finally, a model for vegetable freshness perception that utilizes only luminance cues is presented

Luminance distribution as a determinant for visual freshness perception: Evidence from image analysis of a cabbage leaf

Freshness perception influences consumer behavior when selecting and purchasing fresh foods, such as vegetables and fruits. Although previous research has emphasized the importance of vision when assessing freshness, it remains unknown what specific visual cues control this perception. To investigate which optical parameters are involved in our freshness perception in vegetables, we took digital pictures of the freshness degradation process of cabbages in a controlled environment. Then, we randomly presented color and grayscale versions of those pictures to subjects who had to rate their perceived freshness using a visual analog scale. The results of the freshness perception for both versions of the stimuli were highly correlated proving that using luminance information alone suffices for an accurate estimation of freshness. Moreover, we digitally manipulated the original images only by modifying their luminance distribution and keeping intact their color information. When we presented the resulting images, using the same psycho-physical experimental setting, the subject’s results showed that the perceived freshness also changed concordantly with the changes of the luminance distribution. These results support the hypothesis that the freshness perception of vegetables is highly influenced by the luminance distribution present in that food texture. Furthermore, we propose a model using image and band-pass filter statistics that fitted our results. These findings not only can help design implementations of automatic non-invasive food freshness estimators for the food industry but also represent a way to understand cognitive quality measurements which can be related closely to human perception

Code and data on the categorization of soft-drink bottles using image silhouettes

This data article includes the visual stimuli used to test the categorization of a set of soft drink bottle silhouettes. Additionally, subjects’ perceptual categorization was associated with each visual stimuli. The silhouette of the soft drink bottles was characterized by calculating the most common object shape measurements such as width, height and area and combining them with more complex and specific quantitative shape measurements such as the principal moment statistics. Finally, this data article includes the code for extracting these shape characteristics from image silhouettes. For interpretation and discussion, please see the original article entitled “Quantitative analysis of product categorization in soft drinks using bottle silhouettes” (Arboled and Arce-Lopera, 2015) [1]

Visual palatability of food dishes in color appearance, glossiness and convexo-concave perception depending on light source

This study aims to reveal visual factors which determine the visual palatability of food dishes. We conducted subjective experiments under different light sources, and examined the correlation between the visual palatability and the visual factors, color appearance, glossiness, and convexo-concave perception. We prepared twelve kinds of food dishes, and measured the chromaticity values of all dishes under six kinds of light sources. Next, we transformed the measured data into their respective RGB values. This color management process ensures that the digital images can be displayed with the same chromaticity values as the real objects so that participants can observe the same visual stimuli with no olfactory cues. Twenty participants observed one of the images for one minute, and evaluated the "visual palatability", and answered subjectively three factors, "color appearance", "glossiness" and "convexo-concave perception". As a result, it was revealed that higher correlated color temperature light makes the dishes more palatable, suggesting that the color appearance is an important visual factor for the visual palatability of food dishes. In addition, it was shown that the visual palatability of the raw food dishes and the dishes with sauce can be affected by both color appearance and glossiness depending on the light source