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Rapid Implementation of 3D Facial Reconstruction from a Single Image on an Android Mobile Device
( Phuc Huu Truong ),( Chang-woo Park ),( Minsik Lee ),( Sang-il Choi ),( Sang-hoon Ji ),( And Gu-min Jeong ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.5
In this paper, we propose the rapid implementation of a 3-dimensional (3D) facial reconstruction from a single frontal face image and introduce a design for its application on a mobile device. The proposed system can effectively reconstruct human faces in 3D using an approach robust to lighting conditions, and a fast method based on a Canonical Correlation Analysis (CCA) algorithm to estimate the depth. The reconstruction system is built by first creating 3D facial mapping from a personal identity vector of a face image. This mapping is then applied to real-world images captured with a built-in camera on a mobile device to form the corresponding 3D depth information. Finally, the facial texture from the face image is extracted and added to the reconstruction results. Experiments with an Android phone show that the implementation of this system as an Android application performs well. The advantage of the proposed method is an easy 3D reconstruction of almost all facial images captured in the real world with a fast computation. This has been clearly demonstrated in the Android application, which requires only a short time to reconstruct the 3D depth map.
Truong, Nguyen Tam Nguyen,Nguyen, Hoa,Le, Phuc Huu Tran,Park, Chinho,Jung, Jae Hak Hindawi Limited 2017 Journal of nanomaterials Vol.2017 No.-
<P>ZnO nanorods (Nrods) with ~20–50 nm lengths were synthesized using an aqueous solution of zinc acetate and glacial acetic acid. Bulk heterojunction solar cells were fabricated with the structure of indium tin oxide (ITO)/polyethylenedioxythiophene doped with polystyrene-sulfonic acid (PEDOT:PSS)/ZnO-Nrods + polymer/electron transport layer (ETL)/Al. Current density-voltage characterization of the resulting cells showed that, by adding an ETL and using polymers with a low band gap energy, the photoactive layer surface morphology and the device performance can be dramatically improved.</P>
Phuc Nguyen Thien,Giang Nguyen Thi Huong,An Vu Nguyen Thien Truong,Nam Nguyen Thanh Hoai,Anh Ly Duc,Nguyen Huynh Cam,An Hoang,Phong Mai Thanh,Hieu Nguyen Huu 한국탄소학회 2023 Carbon Letters Vol.33 No.2
In this study, graphene oxide (GO) was synthesized by the improved Hummers’ method. The degree of oxidation from graphite (Gi) to GO was determined through interlayer spacing calculated from X–ray diffraction. Besides, the effect of KMnO4:Gi ratios (X1), H2SO4 volume (X2), oxidation temperature (X3), oxidation time of stage 1 (X4), and oxidation time of stage 2 (X5) was screened by the Plackett–Burman model. The simultaneous impact of three factors that influenced the degree of oxidation (X1, X2, and X3) was studied by the Box–Behnken experimental model of response surface methodology to achieve suitable conditions for the GO synthesis process. The characterization of GO product was investigated via the modern analytical methods: X-ray diffraction, Raman spectroscopy, Fourier transform infrared spectroscopy, UV–Vis spectroscopy, field emission scanning electron microscopy, transmission electron microscopy, and atomic force microscopy. In addition, the study was also carried out on a pilot scale for orientation in industrial application with the yield of 14 g/batch.
Hoan Minh Tran,Tam Huu Nguyen,Viet Quoc Nguyen,Phuc Huynh Tran,Linh Duy Thai,Thuy Thu Truong,Le-Thu T. Nguyen,Ha Tran Nguyen 한국고분자학회 2019 Macromolecular Research Vol.27 No.1
The photoswitching poly(pyrene-1-ylmethyl-methacrylate-random-methyl methacrylate-random-methacrylate spirooxazine) was synthesized via atom transfer radical polymerization and characterized by proton nuclear magnetic resonance (1H NMR), gel permeation chromatography (GPC), Fourier transform infrared (FTIR) spectroscopy, UV-visible spectroscopy, and differential scanning calorimetry (DSC). The obtained copolymer exhibited the capability of erasable and rewritable photoimaging, making it a potential candidate for optical data storage materials. Moreover, the copolymer also showed the sensing ability for cyanide anions effect in aqueous solutions.
Classification of Three Types of Walking Activities Regarding Stairs Using Plantar Pressure Sensors
Jeong, Gu-Min,Truong, Phuc Huu,Choi, Sang-Il IEEE 2017 IEEE SENSORS JOURNAL Vol.17 No.9
<P>In this letter, we propose a novel method for classifying ambulatory activities using eight plantar pressure sensors within smart shoes. Using these sensors, pressure data of participants can be collected regarding level walking, stair descent, and stair ascent. Analyzing patterns of the ambulatory activities, we present new features with which to describe the ambulatory activities. After selecting critical features, a multiclass support vector machine algorithm is applied to classify these activities. Applying the proposed method to the experimental database, we obtain recognition rates up to 95.2% after six steps.</P>
Daily wrist activity classification using a smart band
Nguyen, Nhan Duc,Truong, Phuc Huu,Jeong, Gu-Min IOP PUBLISHING 2017 PHYSIOLOGICAL MEASUREMENT Vol. No.
<P> <I>Objective:</I> In this letter, we propose a novel method for classifying daily wrist activities by using a smart band. <I>Approach:</I> Triaxial acceleration data are collected by built-in sensors of the smart band during experiments regarding five activities, i.e. texting, calling, placing a hand in a pocket, carrying a suitcase, and swinging a hand. We analyze patterns in the sensor signals during these activities based on three types of features, i.e. norm, norm-variance, and frequency-domain features. After extracting the significant features, a multi-class support vector machine algorithm is applied to classify these activities. <I>Main results:</I> We obtained recognition error rates of approximately 2.7% by applying the proposed method to the experimental dataset.</P>
Classification of Five Ambulatory Activities Regarding Stair and Incline Walking Using Smart Shoes
Nguyen, Nhan Duc,Bui, Duong Trong,Truong, Phuc Huu,Jeong, Gu-Min IEEE 2018 IEEE SENSORS JOURNAL Vol.18 No.13
<P>In this paper, we propose a novel method to classify five ambulatory activities, i.e., level ground, incline descent, incline ascent, stair descent, and stair ascent walking using smart shoes which contain eight plantar-pressure sensors on each shoe. Pressure data are collected using an insole-based monitoring system regarding the walking activities conducted by participants at their self-imposed “normal” speed. We present three new features based on an analysis of step patterns to characterize the ambulatory activities and utilize a k-nearest neighbor algorithm to classify the activities from the created features. In experimental results, we obtain walking activity-recognition error rates of 2.16% at the sixth walking step. Furthermore, a proposed method outperforms two reference methods in terms of F1-score and overall accuracy rate.</P>