Contribution of biosignals for emotional analysis on image perception

2016 ◽  
Author(s):  
I. Alexandre ◽  
V. Felizardo ◽  
N. Pombo ◽  
N. Garcia
Keyword(s):  
Image Perception

scholarly journals Interpretation of Swedish Sign Language Using Convolutional Neural Networks and Transfer Learning

2021 ◽  
Vol 2 (3) ◽  
Author(s):  
Gustaf Halvardsson ◽  
Johanna Peterson ◽  
César Soto-Valero ◽  
Benoit Baudry
Keyword(s):  
Neural Networks ◽  
Sign Language ◽  
Transfer Learning ◽  
Convolutional Neural Networks ◽  
Web Application ◽  
Training Dataset ◽  
Motion Processing ◽  
Image Perception ◽  
Sign Languages ◽  
High Level

AbstractThe automatic interpretation of sign languages is a challenging task, as it requires the usage of high-level vision and high-level motion processing systems for providing accurate image perception. In this paper, we use Convolutional Neural Networks (CNNs) and transfer learning to make computers able to interpret signs of the Swedish Sign Language (SSL) hand alphabet. Our model consists of the implementation of a pre-trained InceptionV3 network, and the usage of the mini-batch gradient descent optimization algorithm. We rely on transfer learning during the pre-training of the model and its data. The final accuracy of the model, based on 8 study subjects and 9400 images, is 85%. Our results indicate that the usage of CNNs is a promising approach to interpret sign languages, and transfer learning can be used to achieve high testing accuracy despite using a small training dataset. Furthermore, we describe the implementation details of our model to interpret signs as a user-friendly web application.

scholarly journals Preparatory Experiments Regarding Human Brain Perception and Reasoning of Image Complexity for Synthetic Color Fractal and Natural Texture Images via EEG

2020 ◽  
Vol 11 (1) ◽  
pp. 164
Author(s):  
Irina E. Nicolae ◽  
Mihai Ivanovici
Keyword(s):  
Human Perception ◽  
Event Related Potentials ◽  
Classification Performance ◽  
Subjective Perception ◽  
Image Perception ◽  
Image Complexity ◽  
Temporal Area ◽  
Practical Applications ◽  
Related Potentials ◽  
Texture Complexity

Texture plays an important role in computer vision in expressing the characteristics of a surface. Texture complexity evaluation is important for relying not only on the mathematical properties of the digital image, but also on human perception. Human subjective perception verbally expressed is relative in time, since it can be influenced by a variety of internal or external factors, such as: Mood, tiredness, stress, noise surroundings, and so on, while closely capturing the thought processes would be more straightforward to human reasoning and perception. With the long-term goal of designing more reliable measures of perception which relate to the internal human neural processes taking place when an image is perceived, we firstly performed an electroencephalography experiment with eight healthy participants during color textural perception of natural and fractal images followed by reasoning on their complexity degree, against single color reference images. Aiming at more practical applications for easy use, we tested this entire setting with a WiFi 6 channels electroencephalography (EEG) system. The EEG responses are investigated in the temporal, spectral and spatial domains in order to assess human texture complexity perception, in comparison with both textural types. As an objective reference, the properties of the color textural images are expressed by two common image complexity metrics: Color entropy and color fractal dimension. We observed in the temporal domain, higher Event Related Potentials (ERPs) for fractal image perception, followed by the natural and one color images perception. We report good discriminations between perceptions in the parietal area over time and differences in the temporal area regarding the frequency domain, having good classification performance.

Quality of Life and Body Image Perception in Adolescents: the Contextual Aspects of This Relationship Using Network Analyses

2021 ◽  
Author(s):  
Bruno de Oliveira Pinheiro ◽  
André Luiz Monezi Andrade ◽  
Fernanda Machado Lopes ◽  
Adriana Scatena ◽  
Richard Alecsander Reichert ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Body Image ◽  
Image Perception ◽  
Body Image Perception ◽  
Network Analyses

scholarly journals Percepção da imagem corporal e indicadores antropométricos e de composição corporal associados em idosos

2019 ◽  
Vol 20 (6) ◽  
pp. 525-534
Author(s):  
Iasmim Batista Correia ◽  
Nathalie De Almeida Silva ◽  
Paulo Granges e Silva ◽  
Tarciana Nobre de Menezes
Keyword(s):  
Older Adults ◽  
Body Image ◽  
The Elderly ◽  
Body Image Dissatisfaction ◽  
Normal Weight ◽  
The Body ◽  
Image Perception ◽  
Cross Sectional ◽  
Significance Level ◽  
Body Image Perception

Aging leads to psychological losses and various physical changes that, associated with body-stereotyped patterns imposed by society, can cause disturbances in the body image perception (BIP) in the elderly. The aim of this study was to evaluate BIP in older adults living in the city of Campina Grande / PB and its relationship with different anthropometric and body composition indicators. This cross-sectional study was carried out with older adults of both sexes enrolled in the Family Health Strategy of Campina Grande, PB. BIP was considered as a dependent variable and body mass index (BMI), waist circumference (WC), triceps skinfold (TSF), and arm fat area (AFA) as independent variables. The association between BIP and anthropometric indicators was verified using the Pearson chi-square test (X²), simple and multiple logistic regression, with significance level of p <0.05. Overall, 420 older adults were interviewed (68.1% women), of whom 409 reported their actual body image perception. Regarding the perception of idealized body image, 11 individuals did not respond and 230 were satisfied, since 179 desired another silhouette. Individuals with BMI indicative of overweight / obesity were more likely of showing body image dissatisfaction compared to those with normal weight. Subjects with excessive TSF showed greater body image dissatisfaction in relation to those with normal weight. Women were more likely of showing body image dissatisfaction. Thus, it was observed that variables BMI, TSF and sex were independently associated with body image satisfaction.

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