Do trained assessors generalize their knowledge to new stimuli?
Previous work showed that trained assessors are better at discriminating and describing familiar chemico-sensorial stimuli than novices. In this study, we evaluated whether this superiority holds true for new stimuli. We first trained a group of subjects to characterize beer flavors over a two year period. After training was accomplished, we compared the performance of these trained assessors with the performance of novice subjects for discrimination and matching tasks. The tasks were performed using both well-learned and new beers. Trained assessors outperformed novices in the discrimination task for learned beers but not for new beers. But on the matching task, trained assessors outperfor…
Sort and beer: Everything you wanted to know about the sorting task but did not dare to ask
author cannot archive publisher's version/PDF; International audience; In industries, the sensory characteristics of products are key points to control. The method commonly used to characterize and describe products is the conventional profile. This very efficient method requires a lot of time to train assessors and to teach them how to quantify the sensory characteristics of interest. Over the last few years, other faster and less restricting methods have been developed, such as free choice profile, flash profile, projective mapping or sorting tasks. Among these methods, the sorting task has recently become quite popular in sensory evaluation because of its simplicity: it only requires ass…
Becoming a beer expert: is simple exposure with feedback sufficient to learn beer categories?
Category learning is an important aspect of expertise development which had been little studied in the chemosensory field. The wine literature suggests that through repeated exposure to wines, sensory information is stored by experts as prototypes. The goal of this study was to further explore this issue using beers. We tested the ability of beer consumers to correctly categorize beers from two different categories (top- and bottom-fermented beers) before and after repeated exposure with feedback to beers from these categories. We found that participants learned to identify the category membership of beers to which they have been exposed but were unable to generalize their learning to other…
Connectionist models of face processing: A survey
Abstract Connectionist models of face recognition, identification, and categorization have appeared recently in several disciplines, including psychology, computer science, and engineering. We present a review of these models with the goal of complementing a recent survey by Samal and Iyengar [Pattern Recognition25, 65–77 (1992)] of nonconnectionist approaches to the problem of the automatic face recognition. We concentrate on models that use linear autoassociative networks, nonlinear autoassociative (or compression) and/or heteroassociative backpropagation networks. One advantage of these models over some nonconnectionist approaches is that analyzable features emerge naturally from image-b…
Semantic, typicality and odour representation : a cross-cultural study
International audience
Integrating sensory evaluation into product development: An asian perspective
Edited by Dominique Valentin, Christelle Pêcher, Dzung Hoang Nguyen, Delores Chambers & Hervé Abdi3rd symposium international; Integrating sensory evaluation into product development: An asian perspective. 3. symposium international
Development of a fast panoramic face mosaicking and recognition system
We present some development results on a system that per- forms mosaicking of panoramic faces. Our objective is to study the fea- sibility of panoramic face construction in real time. To do so, we built a simple acquisition system composed of five standard cameras, which together can take simultaneously five views of a face at different angles. Then, we chose an easily hardware-achievable algorithm, consisting of successive linear transformations, in order to compose a panoramic face from these five views. The method has been tested on a large number of faces. In order to validate our system, we also conducted a preliminary study on panoramic face recognition, based on the principal-compone…
Culture and odor categorization : agreement between cultures depends upon the odors
This study evaluated the effect of culture on the relationship between psychological dimensions underlying odor perception and odor categorization. In a first experiment, French, Vietnamese and American participants rated several perceptual dimensions of everyday odorants, and sorted these odorants on the basis of their similarity. Results showed that the three groups of participants differed in their perceptual judgments but agreed in categorizing the odors into four consensual groups (floral, sweet, bad, and nature). Three dimensions––pleasantness, edibility, cosmetic acceptability––discriminated these groups in the same way in the three countries. In a second experiment, the participants…
Quick and dirty but still pretty good: a review of new descriptive methods in food science
Summary For food scientists and industrials, descriptive profiling is an essential tool that involves the evaluation of both the qualitative and quantitative sensory characteristics of a product by a panel. Recently, in response to industrial demands to develop faster and more cost-effective methods of descriptive analysis, several methods have been offered as alternatives to conventional profiling. These methods can be classified in three families: (i) verbal-based methods (flash profile and check-all-that-apply), (ii) similarity-based methods (free sorting task and projective mapping aka Napping®) and (iii) reference-based methods (polarised sensory positioning and pivot profile). We succ…
A Widrow–Hoff Learning Rule for a Generalization of the Linear Auto-associator
Abstract A generalization of the linear auto-associator that allows for differential importance and nonindependence of both the stimuli and the units has been described previously by Abdi (1988). This model was shown to implement the general linear model of multivariate statistics. In this note, a proof is given that the Widrow–Hoff learning rule can be similarly generalized and that the weight matrix will converge to a generalized pseudo-inverse when the learning parameter is properly chosen. The value of the learning parameter is shown to be dependent only upon the (generalized) eigenvalues of the weight matrix and not upon the eigenvectors themselves. This proof provides a unified framew…
DISTATIS: The Analysis of Multiple Distance Matrices
In this paper we present a generalization of classical multidimensional scaling called DISTATIS which is a new method that can be used to compare algorithms when their outputs consist of distance matrices computed on the same set of objects. The method first evaluates the similarity between algorithms using a coefficient called the RV coefficient. From this analysis, a compromise matrix is computed which represents the best aggregate of the original matrices. In order to evaluate the differences between algorithms, the original distance matrices are then projected onto the compromise. We illustrate this method with a "toy example" in which four different "algorithms" (two computer programs …
Arithmetic Problems Formulation and Working Memory Load
First, third, and fifth graders (French children in American-numbered grades) were asked to solve arithmetic problems in which an initial state was modified by two successive transformations. Three independent variables were manipulated systematically. First, the unknown state was either the final state (Sl) or the initial state (S2). Second, either the known state (01) or the transformations (02) appeared in the first place in the problem wording. Third, the question was either located at the end (Ql) or at the beginning (42) of the problem text. As anticipated, these modifications strongly affected the performances at every age: S1 appears clearly easier than S2; 0 1 leads to a better per…
Early-blind individuals show impaired performance in wine odor categorization
International audience; Blind individuals display superior sensory abilities in other modalities, yet results remain contradictory regarding their performance on olfactory tasks. Using complex ecological olfactory tasks, we evaluated the impact of blindness on olfactory performance. We tested 12 early-blind individuals (M = 49, SD = 13.09) and 12 sighted controls (M = 49, SD = 14.31) who were all blindfolded. Based solely on the wine odors, participants evaluated 24 pairs of wine and determined if both samples belonged to the same category (red wine, white wine, or rosé wine) or not (odor categorization), and if so, whether they were identical or not (odor differentiation). Then, they had t…
Multiple factor analysis: principal component analysis for multitable and multiblock data sets
Multiple factor analysis MFA, also called multiple factorial analysis is an extension of principal component analysis PCA tailored to handle multiple data tables that measure sets of variables coll...
Fast Image Mosaicing for Panoramic Face Recognition
In this article, we present some development results of a system that performs mosaicing (or mosaicking) of panoramic faces. Our objective is to study the feasibility of panoramic face construction in real-time. To do so, we built a simple acquisition system composed of 5 standard cameras which, together, can take simultaneously 5 views of a face at different angles. Then, we chose an easily hardware-achievable algorithm, consisting of successive linear transformations, in order to compose a panoramic face from these 5 views. The method has been tested on a relatively large number of faces. In order to validate our system of panoramic face mosaicing, we also conducted a preliminary study on…
STATIS and DISTATIS: optimum multitable principal component analysis and three way metric multidimensional scaling
STATIS is an extension of principal component analysis PCA tailored to handle multiple data tables that measure sets of variables collected on the same observations, or, alternatively, as in a variant called dual-STATIS, multiple data tables where the same variables are measured on different sets of observations. STATIS proceeds in two steps: First it analyzes the between data table similarity structure and derives from this analysis an optimal set of weights that are used to compute a linear combination of the data tables called the compromise that best represents the information common to the different data tables; Second, the PCA of this compromise gives an optimal map of the observation…
Mathématiques pour les sciences cognitives : avec des applications aux réseaux de neurones, au traitement du signal, à l'imagerie cérébrale et à la statistique
Cet ouvrage présente les bases mathématiques sous-jacentes aux sciences cognitives en les intégrant dans des application pertinentes comme les réseaux de neurones, les techniques de l'imagerie cérébrale et la statistique multivariée. Comme les applications importantes pour les sciences cognitives touchent au traitement du signal, à l'informatique et à la statistique, les étudiants et chercheurs de ces domaines pourront aussi s'intéresser au présent ouvrage. Les concepts mathématiques présentés comprennent les notions essentielles du calcul matriciel: (standard, tensoriel de Hadamar, de Kronecker), inverse, pseudo-inverse, décomposition en vecteurs et valeurs propres, décomposition en valeur…
Multiscale Edges Detection by Wavelet Transform for Model of Face Recognition
Publisher Summary The linear auto-associator is a particular case of the linear-associator. The goal of this network is to associate a set of stimuli to itself, which could be used to store and retrieve face images and it also could be applied as a pre-processing device to simulate some psychological tasks—such as categorizing face according to their gender. A technique of learning based on the wavelet transform can improve recognition capability when the pattern images are with a great noise. One of the ways to store and recall face images uses the linear auto-associative memory. This connectionist model is in conjunction with a pixel-based coding of the faces. The image processing using t…
What represents a face? A computational approach for the integration of physiological and psychological data.
Empirical studies of face recognition suggest that faces might be stored in memory by means of a few canonical representations. The nature of these canonical representations is, however, unclear. Although psychological data show a three-quarter-view advantage, physiological studies suggest profile and frontal views are stored in memory. A computational approach to reconcile these findings is proposed. The pattern of results obtained when different views, or combinations of views, are used as the internal representation of a two-stage identification network consisting of an autoassociative memory followed by a radial-basis-function network are compared. Results show that (i) a frontal and a…
A NEURAL NETWORK PRIMER
Neural networks are composed of basic units somewhat analogous to neurons. These units are linked to each other by connections whose strength is modifiable as a result of a learning process or algorithm. Each of these units integrates independently (in paral lel) the information provided by its synapses in order to evaluate its state of activation. The unit response is then a linear or nonlinear function of its activation. Linear algebra concepts are used, in general, to analyze linear units, with eigenvectors and eigenvalues being the core concepts involved. This analysis makes clear the strong similarity between linear neural networks and the general linear model developed by statisticia…
Introduction
Analyzing assessors and products in sorting tasks: DISTATIS, theory and applications
Abstract In this paper we present a new method called distatis that can be applied to the analysis of sorting data. D istatis is a generalization of classical multidimensional scaling which allows one to analyze 3-ways distance tables. When used for analyzing sorting tasks, distatis takes into account individual sorting data. Specifically, when distatis is used to analyze the results of an experiment in which several assessors sort a set of products, we obtain two types of maps: One for the assessors and one for the products. In these maps, the proximity between two points reflects their similarity, and therefore these maps can be read using the same rules as standard metric multidimensiona…
Principal Component and Neural Network Analyses of Face Images: What Can Be Generalized in Gender Classification?
We present an overview of the major findings of the principal component analysis (pca) approach to facial analysis. In a neural network or connectionist framework, this approach is known as the linear autoassociator approach. Faces are represented as a weighted sum of macrofeatures (eigenvectors or eigenfaces) extracted from a cross-product matrix of face images. Using gender categorization as an illustration, we analyze the robustness of this type of facial representation. We show that eigenvectors representing general categorical information can be estimated using a very small set of faces and that the information they convey is generalizable to new faces of the same population and to a l…
A pre-processing technique based on the wavelet transform for linear autoassociators with applications to face recognition
In order to improve the performance of a linear autoassociator (which is a neural network model), we explore the use of several preprocessing techniques. The gist of our approach is to store, in addition to the original pattern, one or several pre-processed (i.e. filtered) versions of the patterns to be stored in a neural network. First, we compare the performance of several pre-processing techniques (a plain vanilla version of the autoassociator as a control, a Sobel operator, a Canny-Deriche operator, and a multiscale Canny-Deriche operator) on an example of a pattern completion task using a noise degraded version of a face stored in an autoassociator. We found that the multiscale Canny-D…
Expertise and typicality: what makes a chardonnay wine a chardonnay
Are wine categories convex? A preliminary study on white and red wine categories
Poster; Are wine categories convex? A preliminary study on white and red wine categories. Wine Active Compounds 2011 International Conference
Sex Classification of Face Areas
Human subjects and an artificial neural network, composed of an autoassociative memory and a perceptron, gender classified the same 160 frontal face images (80 male and 80 female). All 160 face images were presented under three conditions (1) full face image with the hair cropped (2) top portion only of the Condition 1 image (3) bottom portion only of the Condition 1 image. Predictions from simulations using Condition 1 stimuli for training and testing novel stimuli in Conditions 1, 2, and 3, were compared to human subject performance. Although the network showed a fair ability to generalize learning to new stimuli under the three conditions, performing from 66 to 78% correctly on novel fa…
What is the validity of the sorting task for describing beers? A study using trained and untrained assessors
In the sensory evaluation literature, it has been suggested that sorting tasks followed by a description of the groups of products can be used by consumers to describe products, but a closer look at this literature suggests that this claim needs to be evaluated. In this paper, we proposed to examine the validity of the sorting task to describe products by trained and untrained assessors. The experiment reported here consisted in two parts. In a first part, participants sorted nine commercial beers and then described each group with their own words or with a list of terms. In a second part, participants were asked to match each beer with one of their own sets of descriptors. The matching tas…
Semantic, Typicality and Odor Representation: A Cross-cultural Study
This study investigated odor-category organization in three cultures by evaluating (i) the relationship between linguistic and perceptual categorization and (ii) the existence of an internal structure of odor categories. In the first experiment, three groups of 30 participants from American, French and Vietnamese cultures performed a sorting task. The first group sorted 40 odorants on the basis of odor similarity, the second group sorted 40 odor names on the basis of name similarity and the last group sorted 40 odor names on the basis of imagined odor similarity. Results showed that odor categorization was based on perceptual or conceptual similarity and was in part independent of word and …