VNU-UET Repository: No conditions. Results ordered -Date Deposited. 2024-03-28T09:18:36ZEPrintshttp://eprints.uet.vnu.edu.vn/images/sitelogo.pnghttps://eprints.uet.vnu.edu.vn/eprints/2019-12-09T09:26:58Z2019-12-09T09:26:58Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3760This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/37602019-12-09T09:26:58ZRoyal printing woodblocks of Nguyen Dynasty: 3D reconstruction for digital preversationThi Duyen Ngoduyennt@vnu.edu.vnThi Minh TranThi Chau Machaumt@vnu.edu.vnXuan Hung NguyenThanh Ha Leltha@vnu.edu.vn2019-06-20T22:46:05Z2019-06-20T22:46:05Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3524This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/35242019-06-20T22:46:05ZClassifying Non-elementary Movements in Vietnamese Mo DancesThis paper proposes a method to classify non-elementary movements in Vietnamese dances. This classification method uses an OWL ontology called VDM (Vietnamese Dance Movements) recently developed by the authors. The VDM defines a taxonomy of dance move- ment classes and their relationships for the traditional Vietnamese dances taking into account the semantics of its art and its cultural anthropol- ogists. The VDM terminology describes elementary movements (poses) as a dataset ontology importing the ontology VDM. These poses are results of dance sequences segmentation (using segmentation techniques). In this paper, we support the initial ontology VDM by complex classification rules written with SWRL (Semantic Web Rule Language, which is the OWL complementary language) to classify non-elementary movements. The objective is to entail classes of movement phrases, which are non-elementary basic movements with complete meaning and illustrated using M ̃o dances. The classification result is the initial dataset VDM ontology augmented with class descriptions of non-elementary movements, which can be queried using the query language SQWRL (Semantic Query Web-enhanced Rule Language).Mustapha BourahlaAbdelmoutia TelliSalem BenferhatThi Chau Machaumt@vnu.edu.vn2018-11-14T04:34:56Z2018-11-14T04:34:56Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/2648This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/26482018-11-14T04:34:56ZSingle View Image Based – 3D Human Pose ReconstructionTrung Kien HoangKim Hung NguyenThi Chau Machaumt@vnu.edu.vnThi Duyen NgoXuan Thanh Nguyen2018-10-29T04:32:17Z2019-01-07T07:57:19Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3122This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/31222018-10-29T04:32:17ZRegion-based deformation transferMesh deformation is a fundamental technique
for geometric modeling which is applied successfully
in a wide range of applications from shape
design to computer animation. Normally, the deformation
transferred from one actor to another actor is based
on all vertices and triangles of a mesh, leading to timeconsuming
in terms of a 3D sequential model. To address
this problem, we propose a region-based deformation
transfer that automatically identifies several regions with
the largest displacement in time series, and then exploits
those deformations of such regions. Our experimental
results demonstrate that we can obtain the similar deformed
mesh in spite of using approximately 50% – 60%
of the facial area, therefore the time decrease significantly
for deformation transfer step.Khac Phong Dophongdk92@gmail.comThi Chau Machaumt@vnu.edu.vnHoang Giang CaoThi Thu An Nguyen2018-10-29T04:31:03Z2018-10-29T04:31:03Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3123This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/31232018-10-29T04:31:03ZSelecting active frames for action recognition with 3D convolutional networkRecent applications of Convolutional Neural Networks, especially 3-Dimensional Convoltutional Neural Networks (3DCNNs) for human action recognition
(HAR) in videos have widely used. In this paper, we
use a multi-stream framework which is a combination
from separated networks with different kind of input
generated from unique video dataset. To achieve the
high results, firstly, we proposed a method to extract
the active frames (called Selected Active Frames -
SAF) from a videos to build datasets for 3DCNNs in
video classifying problem. Second, we deploy a new
approach called Vote fusion which considered as an
effective fusion method for ensembling multi-stream
networks. From the various datasets generated from
videos, we extract frames by our method and feed
into 3DCNNs for feature extraction, then we carry out
training and then fuse the results of softmax layers
of these streams. We evaluate the proposed methods
on solving action recognition problem. These method
are carried on three well-known datasets (HMFB51,
UCF101, and KTH). The results are also compared to
the state-of-the-art results to illustrate the efficiency
and effectiveness in our approachTieu Binh Hoangbinhhoangtieu@gmail.comThi Chau Machaumt@vnu.edu.vnSugimoto AkihiroThe Duy Buiduybt@vnu.edu.vn2018-08-11T02:19:40Z2018-08-11T02:19:40Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3045This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/30452018-08-11T02:19:40ZAniAge Ontology for Movement Classification in Vietnamese DanceThis paper proposes an OWL ontology called \AniAge", to
define taxonomy of dance movement classes and their relationships for the traditional Vietnamese dance taking into account the semantics of its art and its cultural anthropologists. The \AniAge" terminology can be used to describe elementary movements (poses) as a dataset ontology importing \AniAge". These poses are results of dance sequences segmentation (using segmentation techniques). The ontolgy \AniAge" is supported by classification rules, which are developed with the OWL complementary language SWRL (Semantic Web Rule Language) to entail movement phrases,
which are basic movements with complete meaning. The
dataset ontology containing poses descriptions can be queried using the query language SQWRL (Semantic Query Webenhanced Rule Language), which is extension of SWRL to
retrieve implicit dance knowledge. Then, the query answers
can be used for computer animation.Telli Abdelmoutiatellimoutia@gmail.comThi Chau Machaumt@vnu.edu.vnBourahla MustaphaTabia KarimBenferhat Salem2018-08-03T15:45:03Z2018-08-03T15:45:03Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/3044This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/30442018-08-03T15:45:03ZA Labanotation based ontology for representing Vietnamese folk dancesThis paper aims at designing and constructing an
ontology, representing and allowing Vietnamese folk dances
annotation. An effective approach proposed is based on movement
analysis. It is possible to divide Vietnamese folk dances into basic
units, then movement phrases, movement primitives and dance
poses. Studying deeply Vietnamese folk dances features and
characteristics allows to find out 5 different types of relationships
between main dance components. Typical relationships could be
written in the form of logical predicates. For enriching ontologies,
a formal encoding of the ontology expertise knowledge in the
domain is performed by DL-Lite. The paper uses OWL-2 for
building, organizing and visualizing ontologies. A case study – Mo
folk dance with a knowledge base, is structured simply but
effectively, with reasoning in DL-Lite and answering queries in
SPARQL.Thi Chau Machaumt@vnu.edu.vnThanh Thuy Nguyennguyenthanhthuy@vnu.edu.vn2017-12-08T05:04:25Z2017-12-08T05:04:25Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/2653This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/26532017-12-08T05:04:25ZFacial soft tissue thicknesses prediction using anthropometric distancesPredicting the face of an unidentified individual from its skeletal remains is a difficult matter. Obviously, if the soft tissue thicknesses at every location at the skull are known, we can easily rebuild the face from the skull model. Thus, the problem turns out to be predicting the soft tissue thicknesses for any given skull. With the rapid development of the computer, different techniques are being used in the community for prediction tasks and in recent years the concept of neural networks has emerged as one of them. The principal strength of the neural network is its ability to find patterns and irregularities as well as detecting multi-dimensional non-linear connections in data. In this paper, we propose a method of applying neural networks to predict the soft tissue thicknesses for facial reconstruction. We use the distances between anthropometric locations at the skull as input, and the soft tissue thicknesses as output, as this format is suitable for many machine learning mechanisms. These data is collected and measured from candidates using the Computed Tomography (CT) technique.Quang Huy DinhThi Chau Machaumt@vnu.edu.vnThe Duy Buiduybt@vnu.edu.vnTrong Toan NguyenDinh Tu Nguyen2017-12-08T04:41:03Z2017-12-08T04:43:27Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/2645This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/26452017-12-08T04:41:03ZA Polynomial Algorithm for Merging Lightweight Ontologies in Possibility Theory Under Incommensurability AssumptionBenferhat SalemBouraoui ZiedThi Chau Machaumt@vnu.edu.vnLagrue SylvainRossit Julien2017-12-08T04:40:26Z2017-12-08T04:40:26Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/2646This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/26462017-12-08T04:40:26ZTowards an Ontology for Vietnamese Water PuppetryIn this paper we propose the first steps for building a Vietnamese water puppetry ontology. The creation of the puppetry ontology would allow not only a more informed and productive professional training, but also the capability of preserving and promoting water puppetry. Gathering water puppetry expert knowledge requires a deep study of puppetry history, background knowledge and performance. Hence, we analyze stories, background knowledge and performance of the water puppetry in the context of the Vietnamese general culture and legends. Especially, we emphasize on the issue of inconsistencies - a key challenge in ontology building. We also present a specific case study using DL-Lite for representation, reasoning and querying in presence of inconsistencies.Thi Chau Machaumt@vnu.edu.vnNathalie Chetcuti-SperandioxSylvain LagruexThanh Thuy Nguyennguyenthanhthuy@vnu.edu.vnThe Duy Buiduybt@vnu.edu.vn2017-11-19T09:44:25Z2017-11-19T09:44:25Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/2652This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/26522017-11-19T09:44:25Z3D facial reconstruction system from skull for VietnameseThi Chau Machaumt@vnu.edu.vnDinh Tu NguyenQuang Huy DinhThe Duy Buiduybt@vnu.edu.vn2017-06-10T11:41:14Z2018-01-12T03:14:10Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/2478This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/24782017-06-10T11:41:14ZSingle View Image Based - 3D Human Pose ReconstructionTrung Kien HoangKim Hung NguyenXuan Thanh NguyenThi Chau Machaumt@vnu.edu.vnThi Duyen NgoDuyennt@vnu.edu.vn2016-12-14T10:32:26Z2016-12-14T10:32:26Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/2028This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/20282016-12-14T10:32:26ZKinect based character navigation in VR GameThi Chau Machaumt@vnu.edu.vnMinh Duong Hoang2015-12-28T02:56:36Z2015-12-28T02:56:36Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/1464This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/14642015-12-28T02:56:36ZAn Image based Approach for Speech PerceptionClassification of speech signal is one of the most vital problems in speech perception and spoken word recognition. Although, there have been many studies on the classification of speech signals but the results are still limited. In this paper, we propose an image based approach for speech signal classification based on the combination of Local Naïve Bayes Nearest Neighbor (LNBNN) and Scale-invariant Feature Transform (SIFT) features. The proposed approach allows training feature vectors to have different sizes and no re-training is needed for additional training data after training phase. With this approach, achieved classification results are very satisfactory. They are 72.8, 100 and 95.0 on the ISOLET, Digits and Places databases, respectively.Quang Trung NguyenThe Duy BuiThi Chau Ma2015-01-07T07:52:26Z2017-12-08T04:47:40Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/444This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/4442015-01-07T07:52:26ZEmotional Facial Expression Analysis in the Time DomainEmotions have been studied for a long time and results show that they play an important role in human cognitive functions. In fact, emotions play an extremely important role during the communication between people. And the human face is the most communicative part of the body for expressing emotions; it is recognized that a link exists between facial activity and emotional states. In order to make computer applications more believable and friendly, giving them the ability to recognize and/or express emotions are research fields which have been much focused on. Being able to perform these tasks, firstly, we need to have knowledge about the relationship between emotion and facial activity. Up to now, there have been proposed researches on this relationship. However, almost all these researches focused on analyzing the relationship without taking into account time factors. They analyzed the relationship but did not examined it in the time domain. In this paper, we propose a work on analyzing the relationship between emotions and facial activity in the time domain. Our goal is finding the temporal patterns of facial activity of six basic emotions (happy, sad, angry, fear, surprise, disgust). To perform this task, we analyzed a spontaneous video database in order to consider how facial activities which are related to the six basic emotions happen temporally. From there, we bring out the general temporal patterns for facial expressions of each of the six emotions.Thi Duyen NgoDuyennt@vnu.edu.vnThi Chau Machaumt@vnu.edu.vnThe Duy Buiduybt@vnu.edu.vn2013-01-03T04:12:18Z2017-12-08T04:53:36Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/104This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/1042013-01-03T04:12:18ZShift Error Analysis in Image Based 3D Skull Feature Reconstruction3D skull is crucial in skull-based 3D facial reconstruction. In 3D reconstruction, especially in skull-based 3D facial reconstruction, features usually play an important role. Because, the accuracy in feature detection strongly affects the accuracy of the 3D final model. In this paper, we concentrate on accuracy of 3D reconstructed skull, one important part in skull-based 3D facial reconstruction. We discuss a cause of errors called shift errors when taking sequence of skull images. In addition, we analysis the effect of shift error in 3D reconstruction and propose solution to limit the effect.Thi Chau Machaumt@vnu.edu.vnThe Duy Buiduybt@vnu.edu.vnTrung Kien Dang