30 research outputs found
Face Pose Estimation From Video Sequence Using Dynamic Bayesian Network.
This paper describes a technique to estimate human face pose from colour video sequence using Dynamic Bayesian Network(DBN). As face and facial features trackers usually
track eyes, pupils, mouth corners and skin region(face), our proposed method utilizes merely three of these features – pupils, mouth centre and skin region – to compute the evidence
for DBN inference
Implementation and Revision of the Hirodai Standard 6000 Vocabulary List (HiroTan)
At Hiroshima University, online EFL courses dedicated to vocabulary building have been implemented since 2011, targeting approximately 1,000 undergraduate students each year. As reported in Enokida et al. (2018), an original vocabulary list was developed for these courses, consisting of 6,000 essential English words in daily, business, and academic contexts. A Web-Based Training system was also developed to facilitate online vocabulary learning and to manage learner data. The courses have been successfully implemented since the system’s launch in 2011.
This paper reports on a recent update on the vocabulary list that reflects the latest tendency of the students’ English skills at the university over the past nine years. First, each of the 6,000 words on the list was carefully checked, so relatively unimportant words could be excluded from the list. Then, a total of 1,070 new essential words that are not included in the list were collected from five existing vocabulary lists: The New General Service List and the New Academic Word List (Browne et al., 2013a, 2013b), the TOEIC Service List and the Business Service List (Browne et al., 2016a, 2016b), and TOEIC® L & R Official Vocabulary Book (The Institute for International Business Communication, 2019). These words were rated by a team of five experienced FLaRE instructors on a 5-point scale according to the TOEIC® levels. As a result, 264 new words were selected to be included in the updated version of the list. The latest version of the list will be open to the public in the near future
Hardware-Oriented Algorithm for Human Detection using GMM-MRCoHOG Features
In this research, we focus on Gaussian mixture model-multiresolution co-occurrence histograms of oriented gradients (GMM-MRCoHOG) features using luminance gradients in images and propose a hardware-oriented algorithm of GMM-MRCoHOG to implement it on a field programmable gate array (FPGA). The proposed method simplifies the calculation of luminance gradients, which is a high-cost operation in the conventional algorithm, by using lookup tables to reduce the circuit size. We also designed a human-detection digital architecture of the proposed algorithm for FPGA implementation using high-level synthesis. The verification results showed that the processing speed of the proposed architecture was approximately 123 times faster than that of the FPGA implementation of VGG-16.17th International Joint Conference on Computer Vision Theory and Applications (VISAPP 2022), February 6-8, 2022, Online Streamin
Development of Defect Verification System of IC Lead Frame Surface Using a Ring-lighting
EMoTracker: Eyes and Mouth Tracker Based on Energy Minimization Criterion
We introduce a novel approach for online facial components tracking based on energy minimization criterion. The tracker, known as EMoTracker, employs template matching as the principal technique. As feature appearance changes during tracking, template matching suffers in providing good detection results. Therefore, instead of utilizing only the similarity (correlation values) independently, we add global constraints of facial components placement on face as additional parameters when searching corresponding components. In order to define the correct areas, we first list out n areas (which are the candidates) for eyes and mouth employing template matching technique. These candidates are arranged in high to low correlation order. Selections of correct candidates among these candidates are made based on energy minimization criterion. Additionally, an automatic feature selector and an adaptive face model have been incorporated with EMoTracker to handle tracking from multiple type of faces and non-frontal faces, respectively. Our proposed method also requires no manual initialization and parameter tuning. 1
Real-Time Hand Tracking and Gesture Recognition System
In this paper, we introduce a hand gesture recognition system to recognize real time gesture in unconstrained environments. The system consists of three modules: real time hand tracking, training gesture and gesture recognition using pseudo two dimension hidden Markov models (P2-DHMMs). We have used a Kalman filter and hand blobs analysis for hand tracking to obtain motion descriptors and hand region. It is fairy robust to background cluster and uses skin color for hand gesture tracking and recognition. Furthermore, there have been proposed to improve the overall performance of the approach: (1) Intelligent selection of training images and (2) Adaptive threshold gesture to remove non-gesture pattern that helps to qualify an input pattern as a gesture. A gesture recognition system which can reliably recognize single-hand gestures in real time on standard hardware is developed. In the experiments, we have tested our system to vocabulary of 36 gestures including the America sign language (ASL) letter spelling alphabet and digits, and results effectiveness of the approach
A NEW APPROACH DEDICATED TO REAL-TIME HAND GESTURE RECOGNITION
We introduce a new Pseudo 2-D Hidden Markov Model (P2DHMM) structure dedicated to the time series recognition (T-ComP2DHMM). The T-P2DHMM allows it to do temporal analysis, and to be used in large set of hand gestures movement recognition systems in unconstrained environments. Additionally, robust and flexible hand gesture tracking using an algorithm that combines two powerful stochastic modeling techniques: the first one is pseudo two dimension hidden Markov model (P2DHMM) and the second technique is the wellknown Kalman filter. Our work also present a feature extraction method based on the joint statistics of a subset of DCT coefficients and their position on the hand. Using feature extraction method along with the T-ComP2DHMM structure was used to develop a complete vocabulary of 36 gestures including the America Sign Language (ASL) letter spelling alphabet and digits. The results are effectiveness of the approach
Crystal structure analysis of human serum albumin complexed with sodium 4-phenylbutyrate
Sodium 4-phenylbutyrate (PB) is an orphan drug for the treatment of urea cycle disorders. It also inhibits the development of endoplasmic reticulum stress, the action of histone deacetylases and as a regulator of the hepatocanalicular transporter. PB is generally considered to have the potential for use in the treatment of the diseases such as cancer, neurodegenerative diseases and metabolic diseases. In a previous study, we reported that PB is primarily bound to human serum albumin (HSA) in plasma and its binding site is drug site 2. However, details of the binding mode of PB to HSA remain unknown. To address this issue, we examined the crystal structure of HSA with PB bound to it. The structure of the HSA–PB complex indicates that the binding mode of PB to HSA is quite similar to that for octanoate or drugs that bind to drug site 2, as opposed to that for other medium-chain length of fatty acids. These findings provide useful basic information related to drug–HSA interactions. Moreover, the information presented herein is valuable in terms of providing safe and efficient treatment and diagnosis in clinical settings. Keywords: Human serum albumin, X-ray crystallography, Sodium 4-phenylbutyrate, Drug interaction, Drug site
Supercritical Carbon Dioxide Fluid Leaching (SFL) of Uranium from Solid Wastes Using HNO 3 - tributylphosphate (TBP) Complex as a Reactant
Abstract. Supercritical carbon dioxide (CO 2 ) leaching method (SFL), which is based on the efficient and selective dissolution of UO 2 and U 3 O 8 with supercritical CO 2 containing HNO 3 -tributylphosphate (TBP) complex at 333 K and 15 -20 MPa, has been developed for the removal and recovery of uranium from the solid waste contaminated by uranium oxides. The decontamination factor of UO 2 or U 3 O 8 of higher than 500 were attained by the recommended procedure, which was demonstrated using synthetic solid waste samples of a mixture of the uranium oxides and sea sand