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Main objectives: Computer Vision is a field that includes methods for acquiring, processing, analyzing in order to understand images. Understanding image is a real scientific challenge which presents a lot of open problems. Objectives of our Computer Vision Department are not do deal with all of these problems but to focus on:
• Realizing fundamental researches in visual feature extraction and object representation by introducing new types of feature and/or by combining with other types of feature (multimodal approach);
• Developing real vision based applications, particularly for Vietnam.
Thus the purpose of the Computer Vision Department is twofold. The first one aims assisting the development of Vietnam in areas such as tourism aid, heritage preservation, biodiversity conservation. The second one tries to catch up international level of research in image and video analysis.


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Research tasks and activities: the “Computer Vision” department’s activities are pursued following two main scientific motivations:


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Understanding image and videos: nowadays, with the increasing of technology, cameras are integrated inside many accessories (mobile phone, tablets) or installed at many places (office, store, factories) that make capturing photos, video sequences of everyday life become easier. Although since several decencies, researchers on the world have made a lot of contributions in image / video analysis, automatic understanding of the content of images / videos remains still a real challenge. This comes from the large number of objects in the world, the nature of these objects (fixed / mobile objects, deformable / rigid objects) and the environment as well as the interaction between objects and environment. In addition, as the cameras can be installed at multiple places, the same objects observed at different views may appear very different in the image. Moreover, with the development of technologies, camera could see objects in a larger range of the visible light spectrum (hyper spectral imagine) or the integration of other sensors inside a camera providing easily and low-cost depth information of the object. Understanding image and videos requires fundamental researches on representing object classes in a compact, efficient and discriminated manner, on detecting and tracking multiple objects in the scene and on modeling and recognizing activities in videos. The originality of our researches is to extract features from different data (RGB pr Depth an so on) captured from one or multiple cameras as well as the context information for object and activity/event representation.

Vision based human - machine interaction: at this era, research results in computer vision have came out laboratories and appear in several commercial products to serve human in a everyday life (automatic surveillance system, service robot, surface defect detection system, remote control, etc.). One of our interests is to make these products more usable and familiar for different types of user.

We prefer that the interaction between human and machine should approach the interaction between human and human. To obtain this ambitious objective, we need to study the behavior of human in interacting with machine and then define human - machine interaction protocol. We focus our researches on using multiple channels of communication such as gesture, emotion, voice, specifically aiming at providing a complementary modality for auditory modality for human-machine interaction: visual modality.

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Image processing for Biodiversity
The difficulty encountered by non-botanists when identifying species using standard flora is centred on three major constraints, namely:
• The ability to identify the species;
• The use of dichotomous key;
• The use of difficult technical terms.
In order to minimise and resolve these constraints, we propose two different approaches: interactive and automatic plant identification. With the interactive approach, the users can help the system in selecting object of interest or in refining the plant identification results. Besides, a fusion of multiple organs is proposed to increase the identification accuracy.
Human-Robot interaction
Communications between human and computer become more and more natural and intuitive. Among many modalities of communication, we focus on using hand gestures.
Utilizing hand gesture a is a challenging problem due to the complexity of hand shapes, different lighting conditions, cluttered backgrounds and high computational costs of the vision algorithms. This affects all steps of processing including hand detection, hand posture classification and hand gesture recognition.
Our research focuses on:
- Fast and accurate hand detection with the new feature named “Internal Haar-like features”.
- Robust hand posture classification using improved kernel descriptor.
- Dynamic hand gesture spotting and recognition based on cyclic pattern of posture and manifold learning techniques.

Aids for visually-impaired people
One ambitious goal of the computer vision community is to create new vision system for people with visual impairment. Our department focuses on helping visually-impaired people in indoor navigation and object manipulation through three main core technologies: person localization, obstacle and stair detection and 3D object fitting and modeling.

Toward to applications for Vietnam
Our researchers are working to apply research results to built real vision based prototypes useful to Vietnamese automation industries. Currently, we propose solutions using machine vision techniques in order to help manufacturers to design “made in Vietnam” low-cost products but with high-level functionalities, such as:
• Automatic fabric defect detection;
• Automatic tea flushes assessment, etc.

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Projects in process
- VLIR research program - VIPPA (Visually Impaired People Assistance using multimodal technologies)
- Nafosted-FW0 (Geometric scene analysis as a navigational aid to the visually impaired)
- AUN/SEED-Net project (Medicinal Plant Identification and Collaborative Information System)
- CUI research program (Rice seed assessment using advanced image processing techniques and machine vision tool)

Completed projects
- MOET project (Abnormal event detection using Kinect)
- MOET project (Object detection and recognition in ambient environment)
- LORELA (Localisation Relative personnes/objets en environnements perceptifs pour l'assistance aux personnes Aveugles)
- SYSAPA (Système de Surveillance pour l'Assistance des Personnes Aveugles en
environnement perceptifs)
- CUI research program (Automatizing tea flush assessment by advanced machine vision technique)
- SMART ROBOT (Smart robot guide in museum using multimodal technology)
- AFDD (Automated Fabric Defect Detection system)
- MARVEL (Multimodal Analysis of Recorded Video for E-Learning)
- IRIS (Indexation et Reconnaissance d’Images par la Sémantique)
- SEPIA (Système d’Etude du Patrimoine des Inscriptions Anciennes
du Vietnam)
- MOSAIC (Mobile Search and Annotation using Images in Context)

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Le Thi Lan (Director) – thi-lan.le at
Tran Thi Thanh Hai (Vice-Director) – thanh-hai.tran at
Vu Hai (researcher) – at

Naiscorp Ltd. (Vn)
Norfold Hatexco Ltd. (Vn)
Hanoi University of Agriculture (Vn)
Thai Nguyen University (Vn)
Danang University of Technology (Vn)
Nguyen Dinh Chieu School (Vn)
INRIA Sophia Antipolis (Fr)
L3I (Fr)
LIG (Fr)
NII (Jp)
Ghent University (Be)
University of Strathclyde, Glasgow (UK)
Osaka University (Jp)
KMITL (Thailand)


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page updated July 14, 2016