Group-Level Emotion Recognition Using Transfer Learning From Face Identification
Cornell University Library , 2017. No. 1709.01688.
Alexandr Rassadin, Alexey Gruzdev, Andrey Savchenko
In this paper we describe our algorithmic approach, which was used for submissions in the fifth Emotion Recognition in the Wild (EmotiW 2017) group-level emotion recognition sub-challenge. We extracted feature vectors of detected faces using the Convolutional Neural Network trained for face identification task, rather than traditional pre-training on emotion recognition problems. In the final pipeline an ensemble of Random Forest classifiers was learned to predict emotion score using available training set. In case when the faces have not been detected, one member of our ensemble extracts features from the whole image. During our experimental study, the proposed approach showed the lowest error rate when compared to other explored techniques. In particular, we achieved 75.4% accuracy on the validation data, which is 20% higher than the handcrafted feature-based baseline. The source code using Keras framework is publicly available.
, , , , in : Proceedings of the 19th ACM International Conference on Multimodal Interaction. : [б.и.], 2017. P. 544-548.
In this paper we describe our algorithmic approach, which was used for submissions in the fifth Emotion Recognition in the Wild (EmotiW 2017) group-level emotion recognition sub-challenge. We extracted feature vectors of detected faces using the Convolutional Neural Network trained for face identification task, rather than traditional pre-training on emotion recognition problems. In the final ...
Added: October 18, 2017
Computation-Efficient Face Recognition Algorithm Using a Sequential Analysis of High Dimensional Neural-Net Features
, , Optical Memory and Neural Networks (Information Optics) 2020 Vol. 29 No. 1 P. 19-29
The goal of the study is to increase the computation efficiency of the face recognition that uses feature vectors to describe facial images on photos and videos. These high-dimensional feature vectors are nowadays produced by convolutional neural networks. The methods to aggregate the features generated for each video frame are used to process the video ...
Added: October 25, 2019
Sequential three-way decisions in multi-category image recognition with deep features based on distance factor
, Information Sciences 2019 Vol. 489 P. 18-36
The paper addresses the issue of insufficient speed of image recognition methods if the number of classes is rather large. We propose the novel algorithm based on sequential three-way decisions and a formal description of granular computing. Each image is associated with principal component scores of the high-dimensional features extracted by deep convolution neural network. ...
Added: March 20, 2019
, Записки научных семинаров ПОМИ РАН 2021 Т. 499 С. 267-283
In this paper fast image recognition techniques based on statistical sequential analysis are discussed. We examine the possibility to sequentially process the principal components and organize a convolutional neural net- work with early exits. Particular attention is paid to sequentially learn multi-task lightweight neural network model to predict several facial at- tributes (age, gender and ...
Added: January 27, 2021
Efficient facial representations for age, gender and identity recognition in organizing photo albums using multi-output ConvNet
, PeerJ Computer Science 2019 Vol. 5:e197 P. 1-26
This paper is focused on the automatic extraction of persons and their attributes (gender, year of born) from album of photos and videos. A two-stage approach is proposed in which, firstly, the convolutional neural network simultaneously predicts age/gender from all photos and additionally extracts facial representations suitable for face identification. Here the MobileNet is modified ...
Added: June 12, 2019
, , et al., / Cold Spring Harbor Laboratory. Series 005140 "Biorxiv". 2020.
Electroencephalography (EEG) is a well-established non-invasive technique to measure the brain activity, albeit with a limited spatial resolution. Variations in electric conductivity between different tissues distort the electric fields generated by cortical sources, resulting in smeared potential measurements on the scalp. One needs to solve an ill-posed inverse problem to recover the original neural activity. ...
Added: November 10, 2020
Neural Attention Mechanism and Linear Squeezing of Descriptors in Image Classification for Visual Recommender Systems
, , , Optical Memory and Neural Networks (Information Optics) 2020 Vol. 29 No. 4 P. 297-304
In this paper, we analyze effective methods of multi-label classification of image sets in development of visual recommender systems. We propose a two-step algorithm, which at the first step performs fine-tuning of a convolutional neural network for extraction of visual features. At the second stage, the algorithm concatenates the obtained feature vectors of each image ...
Added: October 25, 2019
, , et al., Journal of Big Data 2019 Vol. 6 Article 73
This study addresses the problem of traffic flow estimation based on the data from a video surveillance camera. Target problem here is formulated as counting and classifying vehicles by their driving direction. This subject area is in early development, and the focus of this work is only one of the busiest crossroads in city Chelyabinsk, ...
Added: December 5, 2020
, , Information Processing and Management 2021 Vol. 58 No. 3 Article 102484
Recently, transfer learning from pre-trained language models has proven to be effective in a variety of natural language processing tasks, including sentiment analysis. This paper aims at identifying deep transfer learning baselines for sentiment analysis in Russian. Firstly, we identified the most used publicly available sentiment analysis datasets in Russian and recent language models which ...
Added: January 28, 2021
Тригонометрическая система функций в проекционных оценках плотности вероятности нейросетевых признаков изображений
, Компьютерная оптика 2018 Т. 42 № 1 С. 149-158
In this paper we study the image recognition tasks, in which images are described by high dimensional feature vectors extracted with deep convolutional neural networks and principal component analysis. In particular, we focus on the problem of high computational complexity of statistical approach with non-parametric estimates of probability density implemented by the probabilistic neural network. ...
Added: April 11, 2018
, , Journal of Physics: Conference Series 2019 Vol. 1368 No. 032016 P. 1-7
In this paper we focus on the problem of user interests’ classification in visual product recommender systems. We propose the two-stage procedure. At first, the visual features are learned by fine-tuning the convolutional neural network, e.g., MobileNet. At the second stage, we use such learnable pooling techniques as neural aggregation network and context gating in ...
Added: November 29, 2019
, , , Pattern Recognition 2022 Vol. 121 Article 108248
In this paper, a user modeling task is examined by processing mobile device gallery of photos and videos. We propose a novel engine for preferences prediction based on scene recognition, object detection and facial analysis. At first, all faces in a gallery are clustered, and all private photos and videos with faces from large clusters ...
Added: August 19, 2021
Unconstrained face identification using maximum likelihood of distances between deep off-the-shelf features
, , Expert Systems with Applications 2018 Vol. 108 P. 170-182
The paper deals with unconstrained face recognition task for the small sample size problem based on computation of distances between high-dimensional off-the-shelf features extracted by deep convolution neural network. We present the novel statistical recognition method, which maximizes the likelihood (joint probabilistic density) of the distances to all reference images from the gallery set. This ...
Added: May 17, 2018
, Information Sciences 2021 Vol. 560 P. 370-385
A novel image recognition algorithm based on sequential three-way decisions is introduced to speed up the inference in a convolutional neural network. In contrast to the majority of existing studies, our approach does not require a special procedure to train a neural network, and thus it can be used with arbitrary architectures including pre-trained convolutional ...
Added: February 25, 2021
Emotion Recognition of a Group of People in Video Analytics Using Deep Off-the-Shelf Image Embeddings
, , , in : Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer Science. Vol. 11179.: Berlin : Springer, 2018. Ch. 19. P. 191-198.
In this paper we address the group-level emotion classification problem in video analytic systems.We propose to apply the MTCNN face detector to obtain facial regions on each video frame. Next, off-the-shelf image features are extracted from each located face using preliminary trained convolutional neural networks. The features of the whole frame are computed as a ...
Added: December 12, 2018
, , Вестник Московского финансово-юридического университета 2017 № 1 С. 200-206
Some questions of scientific visualization are under consideration in this paper. This article also discusses the peculiarities of application of cognitive computer graphics, singles out a range of tasks of scientific visualization. The paper gives a brief overview of modern support tools for program visualization, tendencies of their development and their main characteristics. A module ...
Added: June 10, 2017
, , et al., / НИУ ВШЭ. Series WP BRP "Linguistics". 2015.
Building benchmark corpora in the domain of coreference and anaphora resolution is an important task for developing and evaluating NLP systems and models. Our study is aimed at assessing the feasibility of enhancing corpora with information about coreference relations. The annotation procedure includes identification of text segments that are subjects to annotation (markables), marking their ...
Added: December 15, 2015
, , Computational Mathematics and Modeling 2016 Vol. 27 No. 2 P. 247-253
Added: December 22, 2016
, , et al., Physica A: Statistical Mechanics and its Applications 2014 Vol. 413 No. 1 P. 59-70
A general approach to measure statistical uncertainty of different filtration techniques for market network analysis is proposed. Two measures of statistical uncertainty are introduced and discussed. One is based on conditional risk for multiple decision statistical procedures and another one is based on average fraction of errors. It is shown that for some important cases ...
Added: July 19, 2014
М. : National Instruments Russia, 2017
Содержание сборника составляют доклады с результатами оригинальных исследований и технических решений, ранее не публиковавшиеся. Мы надеемся, что предлагаемый сборник окажется полезным для специалистов, работающих в различных областях науки и техники, для широкого круга преподавателей, аспирантов и студентов ВУЗов, а также для преподавателей средних школ и технических колледжей. ...
Added: May 10, 2017
, , , Inorganic Materials: Applied Research 2016 Vol. 7 No. 1 P. 34-39
A database (DB) on the bandgap of inorganic substances available via the Internet (http://bg.imetdb.ru) was developed for the information service of specialists in the sphere of inorganic chemistry and materials science. The DB is integrated with other information systems on the properties of inorganic substances and materials, which provides the search of a wide range ...
Added: February 23, 2016
, М. : Юрайт, 2016
В настоящее время компьютерные науки стремительно развиваются. Новые версии операционных систем появляются каждые полтора-два года, поэтому было принято решение о включении в данную книгу такого материала, который не будет устаревать. Содержание учебника представляет собой некоторые наиболее общие принципы построения операционных систем, которые были разработаны более 50 лет назад и практически не изменились за прошедшее время. ...
Added: October 13, 2009
Методика самовосстановления распределенной системы контроля и управления техническими объектами на основе методов теории принятия решений
, , , Датчики и системы 2018 Т. 221 № 1 С. 18-24
The article discusses the recovery of distributed control systems of technical objects. The options for the design of subsystems recovery after hardware or software fault of the sensor system are investigated. The development of an integrated subsystems recovery is proposed on the basis of decision-making system to develop the most rational control actions by ...
Added: January 27, 2018
Совершенствование преподавания дисциплин математического цикла на основе инвариантов, необходимых для преподавания курса «Эконометрика» экономистам-бакалаврам
, , Вестник Нижегородского университета им. Н.И. Лобачевского. Серия: Социальные науки 2019 Т. 55 № 3 С. 183-189
The article describes a method that allows to improve the content of disciplines of the mathematical cycle by dividing them into invariant (general) and variable parts. The invariants were identified for such disciplines as «Linear algebra», «Mathematical analysis», «Probability theory and mathematical statistics» delivered to Bachelors program students of economics at several universities. Based on ...
Added: January 28, 2020