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IBISC, France

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16 Papers

Optimization of Tracer Dose for Scintigraphic Imagery

Topics: Biometrics; Medical Signal Acquisition, Analysis and Processing; Neural Networks for Biosignal Data

Authors: C. Bousnah ¹ , S. Anebajagane ² , O. Monsarrat ² , J.-Ph. Conge ¹ , H. Maaref ¹ and V. Vigneron ¹

Affiliations: ¹ IBISC EA 4526, Univ. Evry, Université Paris-Saclay, France , ² Service de Médecine Nucléaire, CHSF, Corbeil, France

Digital Object Identifier: 10.5220/0010822200003123

Proceedings of BIOSIGNALS 2022, ISBN: 978-989-758-552-4

Quick Abstract

Myocardial scintigraphy is a non-invasive isotope examination that has played a central role in the management of these coronary heart diseases for decades.it has proven its performance in nuclear cardiology, mainly for the diagnosis of ischemia by making it possible to analyze the myocardial perfusion, and precisely, to evaluate the quality of the irrigation by the arteries and the coronaries, as well as for the diagnosis of coronary heart disease. It is based on the injection of an intravenous radioactive tracer, which, once injected, is absorbed by the heart muscle. The radiation emitted by the radioactive tracer is converted into an image by computer tomography. However, these scintigraphic images suffer from poor spatial resolution in particular, in obese patients, it is difficult to obtain images of sufficient quality using the recommended standard doses due to the attenuation of γ−rays by soft tissues (fat, fibrous tissues, etc.). This phenomenon prompts the nuclear physician to overdose the tracer and the dose of radiation received exceeds the admissible regulatory limits. In this paper we propose a machine learning model that predict the dose of tracer based on patient’s morphological parameters to obtain images of sufficient quality to support the cardiovascular diagnosis while exposing him to the lowest possible doses of radiation. We show the body weight is not the best-predicting parameter for image quality.

A Depth-based Approach for 3D Dynamic Gesture Recognition

Topics: Image Processing; Vision, Recognition and Reconstruction; Robot Design, Development and Control; Human-Robots Interfaces; Mobile Robots and Autonomous Systems; Engineering Applications

Authors: Hajar Hiyadi ¹ , Fakhreddine Ababsa ² , Christophe Montagne ² , El Houssine Bouyakhf ³ and Fakhita Regragui ³

Affiliations: ¹ Evry Val d’Essonne University and Mohammed V University, France , ² Evry Val d’Essonne University, France , ³ Mohammed V University, Morocco

Digital Object Identifier: 10.5220/0005545401030110

Proceedings of ICINCO 2015, ISBN: 978-989-758-123-6

Quick Abstract

In this paper we propose a recognition technique of 3D dynamic gesture for human robot interaction (HRI) based on depth information provided by Kinect sensor. The body is tracked using the skeleton algorithm provided by the Kinect SDK. The main idea of this work is to compute the angles of the upper body joints which are active when executing gesture. The variation of these angles are used as inputs of Hidden Markov Models (HMM) in order to recognize the dynamic gestures. Results demonstrate the robustness of our method against environmental conditions such as illumination changes and scene complexity due to using depth information only.

Related Ontology Subjects/Areas/Topics (10)

Engineering Applications	Intelligent Control Systems and Optimization	Robotics and Automation
Human-Robots Interfaces	Mobile Robots and Autonomous Systems	Signal Processing, Sensors, Systems Modeling and Control
Image Processing	Robot Design, Development and Control	Vision, Recognition and Reconstruction
Informatics in Control, Automation and Robotics

Automatic Detection of High-voltage Spindles for Parkinson’s Disease

Authors: V. Vigneron ¹ , T. Syed ² and Hsin Chen ³

Affiliations: ¹ Université d’Evry, France , ² National University of Computer and Emerging Sciences, Pakistan , ³ National Tsing Hua University, Taiwan

Digital Object Identifier: 10.5220/0005328503720378

Proceedings of MPBS 2015/BIOSTEC, ISBN: 978-989-758-069-7

Quick Abstract

Parkinson’s disease is a progressive neurodegenerative disorder which can be characterized by several symptoms such as tremor, slowness of movements, bradykinesia/akinesia and absence of postural reflexes . . . and affects 10 million people worldwide. This paper develops a novel strategy for treating patients with PD: silence High-Voltage-Spindle that resemble the pathophysiological b-waves and contribute to the development of b-waves. Silencing HVSs is expected to delay or even prevent the development of b-waves and thus the progression of PD motor symptoms. High-voltage spindles (HVSs) are observed during waking immobility of patients. In this study, the local field potentials collected from the lesioned and control rats on multiple channels were analyzed with an online detection algorithm to identify the characteristic scillations of HVSs from the second-order statistical properties of the signals and the detection performance is investigated to obtain the optimal choices. These results provide further motivation for the real-time implementation of the automatic HVS detection systems with improved performance for pathophysiological and therapeutic applications to the thalamocortical network dysfunctions.

Human-human Collaboration Formalism for Groupware Tailorability in Collaborative Augmented Environments

Topics: Augmented, Mixed and Virtual Environments; Collaborative Augmented, Mixed and Virtual Environments; Distributed Augmented, Mixed and Virtual Reality

Authors: Samir Benbelkacem ¹ , Nadia Zenati-Henda ¹ , Hayet Belghit ¹ , Samir Otmane ² and Abdelkader Bellarbi ³

Affiliations: ¹ Centre de Development Des Technolgies Avancées, Algeria , ² University of Evry, France , ³ Centre de Development Des Technolgies Avancées and University of Evry, Algeria

Digital Object Identifier: 10.5220/0005358604980503

Proceedings of GRAPP 2015/VISIGRAPP, ISBN: 978-989-758-087-1

Quick Abstract

In this paper, human-human collaboration formalism has been proposed to support groupware tailorability for Collaborative Augmented Environments (CAE). Our work is based on the 3C functional model proposed by Ellis. This model decomposes the collaboration into communication, coordination and production. This decomposition has been adapted to design tailorable groupware for CAE. A new concept called “distribution” has been introduced to consider the properties of collaborative and distributed 3D environment. A new formalism integrating this concept is proposed in order to adapt a groupware system to the real need of users evolving in 3D shared scene. Multi-agent technology is, therefore, used to determine the collaboration protocol between humans, through machines, over the network for implementing the desired tailorability.

Related Ontology Subjects/Areas/Topics (4)

Augmented, Mixed and Virtual Environments		Distributed Augmented, Mixed and Virtual Reality		Interactive Environments
Computer Vision, Visualization and Computer Graphics

Towards Pose-free Tracking of Non-rigid Face using Synthetic Data

Topic: Motion and Tracking

Authors: Ngoc-Trung Tran ¹ , Fakhreddine Ababsa ² and Maurice Charbit ³

Affiliations: ¹ Telecom ParisTECH and University of Evry, France , ² University of Evry, France , ³ Telecom ParisTECH, France

Digital Object Identifier: 10.5220/0005179300370044

Proceedings of ICPRAM 2015, ISBN: 978-989-758-077-2

Quick Abstract

The non-rigid face tracking has been achieved many advances in recent years, but most of empirical experiments are restricted at near-frontal face. This report introduces a robust framework for pose-free tracking of non-rigid face. Our method consists of two phases: training and tracking. In the training phase, a large offline synthesized database is built to train landmark appearance models using linear Support Vector Machine (SVM). In the tracking phase, a two-step approach is proposed: the first step, namely initialization, benefits 2D SIFT matching between the current frame and a set of adaptive keyframes to estimate the rigid parameters. The second step obtains the whole set of parameters (rigid and non-rigid) using a heuristic method via pose-wise SVMs. The combination of these aspects makes our method work robustly up to 90° of vertical axial rotation. Moreover, our method appears to be robust even in the presence of fast movements and tracking losses. Comparing to other published algorithms, our method offers a very good compromise of rigid and non-rigid parameter accuracies. This study gives a promising perspective because of the good results in terms of pose estimation (average error is less than 4°on BUFT dataset) and landmark tracking precision (5.8 pixel error compared to 6.8 of one state-of-the-art method on Talking Face video). These results highlight the potential of using synthetic data to track non-rigid face in unconstrained poses.

Related Ontology Subjects/Areas/Topics (8)

Applications	Methodologies and Methods	Pattern Recognition
Computer Vision, Visualization and Computer Graphics	Motion and Tracking	Physiological Computing Systems
Human-Computer Interaction	Motion, Tracking and Stereo Vision

Observer-based controller Design for Remotely Operated Vehicle ROV

Topics: Signal Reconstruction; Robot Design, Development and Control; Vehicle Control Applications; Space and Underwater Robotics; Engineering Applications; Systems Modeling and Simulation; Systems Modeling and Simulation

Authors: Adel Khadhraoui ¹ , Lotfi Beji ¹ , Samir Otmane ¹ and Azgal Abichou ²

Affiliations: ¹ University of Evry, France , ² Polytechnic School of Tunisia, Tunisia

Digital Object Identifier: 10.5220/0005019102000207

Proceedings of ICINCO 2014, ISBN: 978-989-758-039-0

Quick Abstract

This paper presents a method to design an observer-based controller that simultaneously solves global estimation of state and asymptotic stabilization of an underactuated remotely operated vehicle moving in the in three-dimensional. The vehicle does not have a sway and roll actuator and has only position and orientation measurements available. The control development is based on Lyapunov’s direct method for nonlinear system.

Related Ontology Subjects/Areas/Topics (11)

Engineering Applications	Robot Design, Development and Control	Space and Underwater Robotics
Industrial Engineering	Robotics and Automation	Systems Modeling and Simulation
Informatics in Control, Automation and Robotics	Signal Processing, Sensors, Systems Modeling and Control	Vehicle Control Applications
Intelligent Control Systems and Optimization	Signal Reconstruction

3D Interaction Assistance in Virtual Reality: A Semantic Reasoning Engine for Context-awareness - From Interests and Objectives Detection to Adaptations

Topic: Augmented, Mixed and Virtual Environments

Authors: Yannick Dennemont , Guillaume Bouyer , Samir Otmane and Malik Mallem

Affiliation: Evry University, France

Digital Object Identifier: 10.5220/0004207503490358

Proceedings of GRAPP 2013/VISIGRAPP, ISBN: 978-989-8565-46-4

Quick Abstract

This work aims to provide 3D interaction assistance in virtual environments depending on context. We designed and implemented a generic decision engine that can connect to our existing virtual reality applications through a set of tools. It uses an ontology and Conceptual Graphs (CGs) to represent knowledge, and First Order Logic to conduct semantic reasoning. Context information are gathered by virtual sensors in the application and interpreted by the engine. Multimodal assistance is provided by virtual actuators. Our first test scenario is about assistance to selection of objects or navigation towards objects: the engine automatically detects user’s interests and manages adaptations depending on user’s hand gestures, interactions history and type of task.

Related Ontology Subjects/Areas/Topics (3)

Augmented, Mixed and Virtual Environments

Computer Vision, Visualization and Computer Graphics

Interactive Environments

3D Local Binary Pattern for PET Image Classification by SVM - Application to Early Alzheimer Disease Diagnosis

Topics: Biometrics; Medical Image Detection, Acquisition, Analysis and Processing; Image Analysis and Processing

Authors: Christophe Montagne , Andreas Kodewitz , Vincent Vigneron , Virgile Giraud and Sylvie Lelandais

Affiliation: University of Evry, France

Digital Object Identifier: 10.5220/0004226201450150

Proceedings of BIOSIGNALS 2013/BIOSTEC, ISBN: 978-989-8565-36-5

Quick Abstract

The early diagnostic of Alzheimer disease by non-invasive technique becomes a priority to improve the life of patient and his social environment by an adapted medical follow-up. This is a necessity facing the growing number of affected persons and the cost to our society caused by dementia. Computer based analysis of Fluorodeoxyglucose PET scans might become a possibility to make early diagnosis more efficient. Temporal and parietal lobes are the main location of medical findings. We have clues that in PET images these lobes contain more information about Alzheimer’s disease. We used a texture operator, the Local Binary Pattern, to include prior information about the localization of changes in the human brain. We use a Support Vector machine (SVM) to classify Alzheimer’s disease versus normal control group and to get better classification rates focusing on parietal and temporal lobes.

Related Ontology Subjects/Areas/Topics (12)

Applications	Biometrics	Multimedia
Applications and Services	Biometrics and Pattern Recognition	Multimedia Signal Processing
Biomedical Engineering	Computer Vision, Visualization and Computer Graphics	Pattern Recognition
Biomedical Signal Processing	Medical Image Detection, Acquisition, Analysis and Processing	Telecommunications

Bio-inspired Face Authentication using Multiscale LBP

Topics: Biometrics; Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics; Image Analysis and Processing

Authors: Ayoub Elghanaoui ¹ , Nefissa Khiari Hili ² , Christophe Montagne ¹ and Sylvie Lelandais ¹

Affiliations: ¹ Université d'Evry Val d'Essonne, France , ² Université d'Evry Val d'Essonne and University of Tunis El Manar, France

Digital Object Identifier: 10.5220/0004235601820188

Proceedings of BIOSIGNALS 2013/BIOSTEC, ISBN: 978-989-8565-36-5

Quick Abstract

In this paper, we propose a new approach to recognize 2D faces. This approach is based on experiments performed in the field of cognitive science to understand how people recognize a face. To extract features, the image is first decomposed on a base of wavelets using four-level Difference Of Gaussians (DOGs) functions which are a good modeling of human visual system; then different Regions Of Interest (ROIs) are selected on each scale, related to the cognitive method we refer to. After that, Local Binary Patterns (LBP) histograms are computed on each block of the ROIs and concatenated to form the final feature vector. Matching is performed by means of a weighted distance. Weighting coefficients are chosen based on results of psychovisual experiments in which the task assigned to observers was to recognize people. Proposed approach was tested on IV² database and experimental results prove its efficiency when compared to classical face recognition algorithms.

Related Ontology Subjects/Areas/Topics (13)

Applications	Biometrics and Pattern Recognition	Multimedia Signal Processing
Applications and Services	Computer Vision, Visualization and Computer Graphics	Pattern Recognition
Biomedical Engineering	Medical Image Detection, Acquisition, Analysis and Processing	Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics
Biomedical Signal Processing	Multimedia	Telecommunications
Biometrics

Mobile Robot Localization based on a Set Approach using Heterogeneous Measurements

Topics: Mobile Robots and Autonomous Systems; Sensors Fusion

Authors: Etienne Colle , Simon Galerne and Maxime Jubert

Affiliation: University Of Evry, France

Digital Object Identifier: 10.5220/0004427401300139

Proceedings of ICINCO 2013, ISBN: 978-989-8565-71-6

Quick Abstract

Related Ontology Subjects/Areas/Topics (5)

Informatics in Control, Automation and Robotics		Robotics and Automation		Signal Processing, Sensors, Systems Modeling and Control
Mobile Robots and Autonomous Systems		Sensors Fusion

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