scholarly journals Optimal Geometrical Set for Automated Marker Placement to Virtualized Real-Time Facial Emotions

PLoS ONE ◽  
2016 ◽  
Vol 11 (2) ◽  
pp. e0149003 ◽  
Author(s):  
Vasanthan Maruthapillai ◽  
Murugappan Murugappan
Keyword(s):  
Real Time ◽  
Facial Emotions

scholarly journals Real-Time Facial Emotion Recognition Framework for Employees of Organizations Using Raspberry-Pi

2021 ◽  
Vol 11 (22) ◽  
pp. 10540
Author(s):  
Navjot Rathour ◽  
Zeba Khanam ◽  
Anita Gehlot ◽  
Rajesh Singh ◽  
Mamoon Rashid ◽  
...  
Keyword(s):  
Emotion Recognition ◽  
Real Time ◽  
Real Life ◽  
Recognition System ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Raspberry Pi ◽  
Input Device ◽  
Facial Emotions ◽  
Deep Network

There is a significant interest in facial emotion recognition in the fields of human–computer interaction and social sciences. With the advancements in artificial intelligence (AI), the field of human behavioral prediction and analysis, especially human emotion, has evolved significantly. The most standard methods of emotion recognition are currently being used in models deployed in remote servers. We believe the reduction in the distance between the input device and the server model can lead us to better efficiency and effectiveness in real life applications. For the same purpose, computational methodologies such as edge computing can be beneficial. It can also encourage time-critical applications that can be implemented in sensitive fields. In this study, we propose a Raspberry-Pi based standalone edge device that can detect real-time facial emotions. Although this edge device can be used in variety of applications where human facial emotions play an important role, this article is mainly crafted using a dataset of employees working in organizations. A Raspberry-Pi-based standalone edge device has been implemented using the Mini-Xception Deep Network because of its computational efficiency in a shorter time compared to other networks. This device has achieved 100% accuracy for detecting faces in real time with 68% accuracy, i.e., higher than the accuracy mentioned in the state-of-the-art with the FER 2013 dataset. Future work will implement a deep network on Raspberry-Pi with an Intel Movidious neural compute stick to reduce the processing time and achieve quick real time implementation of the facial emotion recognition system.

scholarly journals A fuzzy logic approach to reliable real-time recognition of facial emotions

2019 ◽  
Vol 78 (14) ◽  
pp. 18943-18966 ◽  
Author(s):  
Kiavash Bahreini ◽  
Wim van der Vegt ◽  
Wim Westera
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Facial Emotions ◽  
Fuzzy Logic Approach ◽  
Logic Approach

Some Recent Results in Quiescent Prominence Spectrometry

1979 ◽  
Vol 44 ◽  
pp. 41-47
Author(s):  
Donald A. Landman
Keyword(s):  
Real Time ◽  
Computer System ◽  
Spectral Response ◽  
Absolute Intensity ◽  
Solar Observatory ◽  
Target Size ◽  
Small Target ◽  
Signal Averaging ◽  
Quiescent Prominence

This paper describes some recent results of our quiescent prominence spectrometry program at the Mees Solar Observatory on Haleakala. The observations were made with the 25 cm coronagraph/coudé spectrograph system using a silicon vidicon detector. This detector consists of 500 contiguous channels covering approximately 6 or 80 Å, depending on the grating used. The instrument is interfaced to the Observatory’s PDP 11/45 computer system, and has the important advantages of wide spectral response, linearity and signal-averaging with real-time display. Its principal drawback is the relatively small target size. For the present work, the aperture was about 3″ × 5″. Absolute intensity calibrations were made by measuring quiet regions near sun center.

Video real-time imaging of artificial membranes during freeze-drying by cryo-electron microscopy

1988 ◽  
Vol 46 ◽  
pp. 16-17
Author(s):  
Alan S. Rudolph ◽  
Ronald R. Price
Keyword(s):  
Real Time ◽  
Self Assembly ◽  
Freeze Drying ◽  
Video Capture ◽  
Drying Process ◽  
Artificial Membranes ◽  
The Past ◽  
Cryo Electron Microscopy ◽  
Spherical Structures ◽  
Capture Techniques

We have employed cryoelectron microscopy to visualize events that occur during the freeze-drying of artificial membranes by employing real time video capture techniques. Artificial membranes or liposomes which are spherical structures within internal aqueous space are stabilized by water which provides the driving force for spontaneous self-assembly of these structures. Previous assays of damage to these structures which are induced by freeze drying reveal that the two principal deleterious events that occur are 1) fusion of liposomes and 2) leakage of contents trapped within the liposome [1]. In the past the only way to access these events was to examine the liposomes following the dehydration event. This technique allows the event to be monitored in real time as the liposomes destabilize and as water is sublimed at cryo temperatures in the vacuum of the microscope. The method by which liposomes are compromised by freeze-drying are largely unknown. This technique has shown that cryo-protectants such as glycerol and carbohydrates are able to maintain liposomal structure throughout the drying process.

An Interactive Minicomputer Program for the Indexing and Simulation of Electron Diffraction Patterns

1976 ◽  
Vol 34 ◽  
pp. 542-543
Author(s):  
R.P. Goehner ◽  
W.T. Hatfield ◽  
Prakash Rao
Keyword(s):  
Electron Diffraction ◽  
Real Time ◽  
Pattern Analysis ◽  
Flow Diagram ◽  
Hard Copy ◽  
Time Analysis ◽  
Real Time Analysis ◽  
Transmission Electron ◽  
One Step ◽  
Diffraction Patterns

Computer programs are now available in various laboratories for the indexing and simulation of transmission electron diffraction patterns. Although these programs address themselves to the solution of various aspects of the indexing and simulation process, the ultimate goal is to perform real time diffraction pattern analysis directly off of the imaging screen of the transmission electron microscope. The program to be described in this paper represents one step prior to real time analysis. It involves the combination of two programs, described in an earlier paper(l), into a single program for use on an interactive basis with a minicomputer. In our case, the minicomputer is an INTERDATA 70 equipped with a Tektronix 4010-1 graphical display terminal and hard copy unit.A simplified flow diagram of the combined program, written in Fortran IV, is shown in Figure 1. It consists of two programs INDEX and TEDP which index and simulate electron diffraction patterns respectively. The user has the option of choosing either the indexing or simulating aspects of the combined program.

Microstructural investigation of surface roughness in MBE-grown AlAs

1995 ◽  
Vol 53 ◽  
pp. 454-455
Author(s):  
R. Rajesh ◽  
R. Droopad ◽  
C. H. Kuo ◽  
R. W. Carpenter ◽  
G. N. Maracas
Keyword(s):  
Thin Film ◽  
Real Time ◽  
Growth Control ◽  
Native Oxide ◽  
Effusion Cell ◽  
Surface Oxide Layer ◽  
Microstructural Investigation ◽  
Mbe Growth ◽  
Film Substrate ◽  
And Control

Knowledge of material pseudodielectric functions at MBE growth temperatures is essential for achieving in-situ, real time growth control. This allows us to accurately monitor and control thicknesses of the layers during growth. Undesired effusion cell temperature fluctuations during growth can thus be compensated for in real-time by spectroscopic ellipsometry. The accuracy in determining pseudodielectric functions is increased if one does not require applying a structure model to correct for the presence of an unknown surface layer such as a native oxide. Performing these measurements in an MBE reactor on as-grown material gives us this advantage. Thus, a simple three phase model (vacuum/thin film/substrate) can be used to obtain thin film data without uncertainties arising from a surface oxide layer of unknown composition and temperature dependence.In this study, we obtain the pseudodielectric functions of MBE-grown AlAs from growth temperature (650°C) to room temperature (30°C). The profile of the wavelength-dependent function from the ellipsometry data indicated a rough surface after growth of 0.5 μm of AlAs at a substrate temperature of 600°C, which is typical for MBE-growth of GaAs.

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