Spatio-Temporal Facial Expression Recognition Using Convolutional Neural Networks and Conditional Random Fields

Automated Facial Expression Recognition (FER) has been a challenging task for decades. Many of the existing works use hand-crafted features such as LBP, HOG, LPQ, and Histogram of Optical Flow (HOF) combined with classifiers such as Support Vector Machines for expression recognition. These methods often require rigorous hyperparameter tuning to achieve good results. Recently Deep Neural Networks (DNN) have shown to outperform traditional methods in visual object recognition. In this paper, we propose a two-part network consisting of a DNN-based architecture followed by a Conditional Random Field (CRF) module for facial expression recognition in videos. The first part captures the spatial relation within facial images using convolutional layers followed by three Inception-ResNet modules and two fully-connected layers. To capture the temporal relation between the image frames, we use linear chain CRF in the second part of our network. We evaluate our proposed network on three publicly available databases, viz. CK+, MMI, and FERA. Experiments are performed in subject-independent and cross-database manners. Our experimental results show that cascading the deep network architecture with the CRF module considerably increases the recognition of facial expressions in videos and in particular it outperforms the state-of-the-art methods in the cross-database experiments and yields comparable results in the subject-independent experiments.Comment: To appear in 12th IEEE Conference on Automatic Face and Gesture Recognition Worksho

Facial Expression Recognition Using Enhanced Deep 3D Convolutional Neural Networks

Deep Neural Networks (DNNs) have shown to outperform traditional methods in various visual recognition tasks including Facial Expression Recognition (FER). In spite of efforts made to improve the accuracy of FER systems using DNN, existing methods still are not generalizable enough in practical applications. This paper proposes a 3D Convolutional Neural Network method for FER in videos. This new network architecture consists of 3D Inception-ResNet layers followed by an LSTM unit that together extracts the spatial relations within facial images as well as the temporal relations between different frames in the video. Facial landmark points are also used as inputs to our network which emphasize on the importance of facial components rather than the facial regions that may not contribute significantly to generating facial expressions. Our proposed method is evaluated using four publicly available databases in subject-independent and cross-database tasks and outperforms state-of-the-art methods.Comment: To appear in 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW

Facial Expression Recognition from World Wild Web

Recognizing facial expression in a wild setting has remained a challenging task in computer vision. The World Wide Web is a good source of facial images which most of them are captured in uncontrolled conditions. In fact, the Internet is a Word Wild Web of facial images with expressions. This paper presents the results of a new study on collecting, annotating, and analyzing wild facial expressions from the web. Three search engines were queried using 1250 emotion related keywords in six different languages and the retrieved images were mapped by two annotators to six basic expressions and neutral. Deep neural networks and noise modeling were used in three different training scenarios to find how accurately facial expressions can be recognized when trained on noisy images collected from the web using query terms (e.g. happy face, laughing man, etc)? The results of our experiments show that deep neural networks can recognize wild facial expressions with an accuracy of 82.12%

The Effects of Different Roughness Configurations on Aerodynamic Performance of Wind Turbine Airfoil and Blade

In this research, viscous and turbulent flow is simulated numerically on an E387 airfoil as well as on a turbine blade. The main objective of this paper is to investigate various configurations of roughness to find a solution in order to mitigate roughness destructive impacts. Hence, the sand grain roughness is distributed uniformly along pressure side, suction side and both sides during the manufacturing process. Navier-Stokes equations are discretized by the finite volume method and are solved by SIMPLE algorithm. Results indicated that in contrast with previous studies, the roughness will be useful if it is applied on only pressure side of the airfoil. In this condition, the lift coefficient is increased to and 1.2% compare to the airfoil with rough and smooth sides, respectively. However, in 3-D simulation, the lift coefficient of the blade with pressure surface roughness is less than smooth blade, but still its destructive impacts are much less than of both surfaces roughness and suction surfaces roughness. Therefore, it can be deduced that in order to reveal the influence of roughness, the simulation must be accomplished in three dimensions.Article History: Received Jun 12th 2017; Received in revised form August 27th 2017; Accepted Oct 3rd 2017; Available onlineHow to Cite This Article: Jafari, K., Djavareshkian, M.H., Feshalami, B.H. (2017) The Effects of Different Roughness Configurations on Aerodynamic Performance of Wind Turbine Airfoil and Blade. International Journal of Renewable Energy Develeopment, 6(3), 273-281.https://doi.org/10.14710/ijred.6.3.273-28

Anti-Candida activity of ethanolic extracts of Iranian endemic medicinal herbs against Candida albicans

It has long been known that herbs and their extracts have antimicrobial activities. Heracleum lasiopetalum Boiss., Satureja bachtiarica Bunge., Thymus daenensis Celak., Echiophora platyloba L., Dracocephalum multicaule Benth., Kelussia odoratissima Mozaff. and Achillea kellalensis Boiss. are Iranian endemic plant species that have been traditionally used as medicinal herbs and spices in different regions of Iran especially Central Zagross. Seven ethanolic extracts of endemic medicinal herbs and one extract of native medicinal herb (Stachys lavandulifolia Vahl.) collected from Chaharmahal va Bakhtiari province of Iran were assayed for the in vitro antifungal activity against Candida albicans (ATCC1023), using agar dilution methods. Most of the extracts showed relatively high anti-Candida activity against the tested fungi with the diameter of inhibition zone ranging between 8 and 17 mm. The extracts of S. bachtiarica and T. daenensis exhibited high inhibitory effect against C. albicans. The extracts of S. bachtiarica and T. daenensis were characterized using HPLC, the major components of S. bachtiarica and T. daenensis were carvacrol and thymol, respectively. The minimum inhibitory concentration (MIC) values for active extract range between 25 and 50 µg/ml. In conclusion, it can be said that the extract of some of the Iranian endemic medicinal plants (S. bachtiarica and T. daenensis) could be used as natural anti-Candida

Entanglement Capacity of Nonlocal Hamiltonians : A Geometric Approach

We develop a geometric approach to quantify the capability of creating entanglement for a general physical interaction acting on two qubits. We use the entanglement measure proposed by us for $N$-qubit pure states (PRA \textbf{77}, 062334 (2008)). Our procedure reproduces the earlier results (PRL \textbf{87}, 137901 (2001)). The geometric method has the distinct advantage that it gives an experimental way to monitor the process of optimizing entanglement production.Comment: 8 pages, 1 figure

Inductive Construction of 2-Connected Graphs for Calculating the Virial Coefficients

In this paper we give a method for constructing systematically all simple 2-connected graphs with n vertices from the set of simple 2-connected graphs with n-1 vertices, by means of two operations: subdivision of an edge and addition of a vertex. The motivation of our study comes from the theory of non-ideal gases and, more specifically, from the virial equation of state. It is a known result of Statistical Mechanics that the coefficients in the virial equation of state are sums over labelled 2-connected graphs. These graphs correspond to clusters of particles. Thus, theoretically, the virial coefficients of any order can be calculated by means of 2-connected graphs used in the virial coefficient of the previous order. Our main result gives a method for constructing inductively all simple 2-connected graphs, by induction on the number of vertices. Moreover, the two operations we are using maintain the correspondence between graphs and clusters of particles.Comment: 23 pages, 5 figures, 3 table

Variations of the McEliece Cryptosystem

Two variations of the McEliece cryptosystem are presented. The first one is based on a relaxation of the column permutation in the classical McEliece scrambling process. This is done in such a way that the Hamming weight of the error, added in the encryption process, can be controlled so that efficient decryption remains possible. The second variation is based on the use of spatially coupled moderate-density parity-check codes as secret codes. These codes are known for their excellent error-correction performance and allow for a relatively low key size in the cryptosystem. For both variants the security with respect to known attacks is discussed