mohamed NEJI - Academia.edu (original) (raw)

Papers by mohamed NEJI

Research paper thumbnail of Dress-up: deep neural framework for image-based human appearance transfer

Multimedia Tools and Applications

The fashion industry is at the brink of radical transformation. The emergence of Artificial Intel... more The fashion industry is at the brink of radical transformation. The emergence of Artificial Intelligence (AI) in fashion applications creates many opportunities for this industry and make fashion a better space for everyone. Interesting to this matter, we proposed a virtual try-on interface to stimulate consumers purchase intentions and facilitate their online buying decision process. Thus, we present, in this paper, our flexible person generation system for virtual try-on that aiming to treat the task of human appearance transfer across images while preserving texture details and structural coherence of the generated outfit. This challenging task has drawn increasing attention and made huge development of intelligent fashion applications. However, it requires different challenges, especially in the case of a wide divergences between the source and target images. To solve this problem, we proposed a flexible person generation framework called Dress-up to treat the 2D virtual try-on task. Dress-up is an end-to-end generation pipeline with three modules based on the task of image-toimage translation aiming to sequentially interchange garments between images, and produce dressing effects not achievable by existing works. The core idea of our solution is to explicitly encode the body pose and the target clothes by a pre-processing module based on the semantic segmentation process. Then, a conditional adversarial network is implemented to generate target segmentation feeding respectively, to the alignment and translation networks to generate the final output results. The novelty of this work lies in realizing the appearance transfer across images with high quality by reconstructing garments on a person in different orders and looks from simlpy semantic maps and 2D images without using 3D modeling. Our system can produce dressing effects and provide significant results over the state-ofthe-art methods on the widely used DeepFashion dataset. Extensive evaluations show that Dress-up outperforms other recent methods in terms of output quality, and handles a wide range of editing functions for which there is no direct supervision. Different types of results were computed to verify the performance of our proposed framework and show that the robustness and effectiveness are high by utilizing our method.

Research paper thumbnail of You can Try without Visiting: A Comprehensive Survey on Virtually Try-on Outfits

Our work aims to conduct a comprehensive literature review of deep learning methods applied in th... more Our work aims to conduct a comprehensive literature review of deep learning methods applied in the fashion industry and, especially, the image-based virtual fitting task by citing research works published in the last years. We have summarized their challenges, their main frameworks, the popular benchmark datasets, and the different evaluation metrics. Also, some promising future research directions are discussed to propose improvements in this research field.

Research paper thumbnail of Image-Based Virtual Try-on System: A Survey of Deep Learning-Based Methods

Our work aims to conduct a comprehensive literature review of deep learning methods applied in th... more Our work aims to conduct a comprehensive literature review of deep learning methods applied in the fashion industry and, especially, the image-based virtual fitting task by citing research works published in the last years. We have summarized their challenges, their main frameworks, the popular benchmark datasets, and the different evaluation metrics. Also, some promising future research directions are discussed to propose improvements in this research field.

Research paper thumbnail of A new approach for a safe car assistance system

2015 4th International Conference on Advanced Logistics and Transport (ICALT), 2015

Drowsiness, which is the state when drivers do not have scheduled breaks while traveling long dis... more Drowsiness, which is the state when drivers do not have scheduled breaks while traveling long distances, is the main reason behind serious motorway accidents. Accordingly, experts claim that drowsy state is hard to be recognized early enough to prevent serious accidents that may lead even to road deaths. In this work, we propose a new drowsiness state detection system based on physiological signals and eye blinking. An experiment has been directed to justify the utility of the proposed approach. This system uses a smart video camera that takes drivers faces images and supervises the eye blink (open and close); also, it uses the Emotiv EPOC headset to acquire the electroencephalogram (EEG) signals. Eye detection is done by Viola and Jones technique, EEG. Finally, we have chosen the fuzzy logic techniques to classify the EEG signals and eye blinking detection to analyze the results.

Research paper thumbnail of Multidimensional Schema Evolution - Integrating New OLAP Requirements

International Conference on Enterprise Information Systems, 2006

Multidimensional databases are an effective support for OLAP processes. They improve the enterpri... more Multidimensional databases are an effective support for OLAP processes. They improve the enterprise decision-making. These databases evolve with the decision maker requirements evolution and, are sensitive to data source changes. In this paper, we are interested in the evolution of the data mart schema due to the raise of new OLAP needs. Our approach determines first, what functional data marts will be able to cover a new requirement, if any, and secondly, decides on a strategy of integration. This leads either to the alteration of an existing data mart schema or, to the creation of a new schema suitable for the new requirement.

Research paper thumbnail of The Multi-Agents Architecture for Emotion Recognition

International Journal of Software Innovation, 2014

The author's research focuses on the problem of Information Retrieval System (IRS) that integ... more The author's research focuses on the problem of Information Retrieval System (IRS) that integrates the human emotion recognition. This system must be able to recognize the degree of satisfaction of the user for the result found through its facial expression, its physiological state, its gestures and its voice. This paper is an algorithm for recognizing the emotional state of a user during a search session in order to issue the relevant documents that the user needs. The authors also present the architecture agent of the envisaged system and the organizational model.

Research paper thumbnail of Feast: face and emotion analysis system for smart tablets

Multimedia Tools and Applications, 2014

ABSTRACT Face and emotion recognition is still an open and very challenging problem. This paper p... more ABSTRACT Face and emotion recognition is still an open and very challenging problem. This paper presents a system FEAST which is an intelligent control system of Smart Tablets. It involves manipulating user sessions to adapt the working environment to his emotional state. First, a face detection followed by face and emotion recognition is performed, then a profile change is made basing on the obtained results. The face detection is based on skin color and geometric moments and face recognition is done by merging two features spaces, namely, Zernike moments and EAR-LBP. A feature selection technique reducing the parameter space size is applied. The same parameters are used for the emotion recognition.

Research paper thumbnail of Towards an intelligent information research system based on the human behavior: Recognition of user emotional state

ABSTRACT Our works deals with the problem of Information Retrieval System (IRS) that integrates t... more ABSTRACT Our works deals with the problem of Information Retrieval System (IRS) that integrates the human behaviour. This system must be able to recognize the degree of satisfaction of the user of the result found through its facial expression, its physiological state, its gestures and its voice. For this, we propose in this paper an algorithm for recognizing the emotional state of a user during a search session in order to issue the relevant documents that he needs. We present also, the architecture agent of the envisaged system.

Research paper thumbnail of Real-time affective learner profile analysis using an EMASPEL framework

Page 1. Real-time affective learner profile analysis using an EMASPEL framework Mohamed Neji, Moh... more Page 1. Real-time affective learner profile analysis using an EMASPEL framework Mohamed Neji, Mohamed Ben Ammar, Adel M. Alimi Research Group on Intelligent Machines University of Sfax, National school of engineers (ENIS), BP1173, Sfax, 3038, Tunisia. ...

Research paper thumbnail of Emotion recognition by analysis of EEG signals

13th International Conference on Hybrid Intelligent Systems (HIS 2013), 2013

ABSTRACT We propose in this paper an emotional recognition system based on physiological signals.... more ABSTRACT We propose in this paper an emotional recognition system based on physiological signals. We adopt the seven basic emotions that are: neutrality, joy, sadness, fear, anger, disgust and surprise. An experiment has been conducted to verify the feasibility of the proposed system. This experience has allowed us to acquire EEG signals and to create an emotional database. For this, we have used the Emotiv EPOC headset. Thereafter, we have chosen the fuzzy logic techniques to classify the EEG signals and to analyze the results.

Research paper thumbnail of Dress-up: deep neural framework for image-based human appearance transfer

Multimedia Tools and Applications

The fashion industry is at the brink of radical transformation. The emergence of Artificial Intel... more The fashion industry is at the brink of radical transformation. The emergence of Artificial Intelligence (AI) in fashion applications creates many opportunities for this industry and make fashion a better space for everyone. Interesting to this matter, we proposed a virtual try-on interface to stimulate consumers purchase intentions and facilitate their online buying decision process. Thus, we present, in this paper, our flexible person generation system for virtual try-on that aiming to treat the task of human appearance transfer across images while preserving texture details and structural coherence of the generated outfit. This challenging task has drawn increasing attention and made huge development of intelligent fashion applications. However, it requires different challenges, especially in the case of a wide divergences between the source and target images. To solve this problem, we proposed a flexible person generation framework called Dress-up to treat the 2D virtual try-on task. Dress-up is an end-to-end generation pipeline with three modules based on the task of image-toimage translation aiming to sequentially interchange garments between images, and produce dressing effects not achievable by existing works. The core idea of our solution is to explicitly encode the body pose and the target clothes by a pre-processing module based on the semantic segmentation process. Then, a conditional adversarial network is implemented to generate target segmentation feeding respectively, to the alignment and translation networks to generate the final output results. The novelty of this work lies in realizing the appearance transfer across images with high quality by reconstructing garments on a person in different orders and looks from simlpy semantic maps and 2D images without using 3D modeling. Our system can produce dressing effects and provide significant results over the state-ofthe-art methods on the widely used DeepFashion dataset. Extensive evaluations show that Dress-up outperforms other recent methods in terms of output quality, and handles a wide range of editing functions for which there is no direct supervision. Different types of results were computed to verify the performance of our proposed framework and show that the robustness and effectiveness are high by utilizing our method.

Research paper thumbnail of You can Try without Visiting: A Comprehensive Survey on Virtually Try-on Outfits

Our work aims to conduct a comprehensive literature review of deep learning methods applied in th... more Our work aims to conduct a comprehensive literature review of deep learning methods applied in the fashion industry and, especially, the image-based virtual fitting task by citing research works published in the last years. We have summarized their challenges, their main frameworks, the popular benchmark datasets, and the different evaluation metrics. Also, some promising future research directions are discussed to propose improvements in this research field.

Research paper thumbnail of Image-Based Virtual Try-on System: A Survey of Deep Learning-Based Methods

Our work aims to conduct a comprehensive literature review of deep learning methods applied in th... more Our work aims to conduct a comprehensive literature review of deep learning methods applied in the fashion industry and, especially, the image-based virtual fitting task by citing research works published in the last years. We have summarized their challenges, their main frameworks, the popular benchmark datasets, and the different evaluation metrics. Also, some promising future research directions are discussed to propose improvements in this research field.

Research paper thumbnail of A new approach for a safe car assistance system

2015 4th International Conference on Advanced Logistics and Transport (ICALT), 2015

Drowsiness, which is the state when drivers do not have scheduled breaks while traveling long dis... more Drowsiness, which is the state when drivers do not have scheduled breaks while traveling long distances, is the main reason behind serious motorway accidents. Accordingly, experts claim that drowsy state is hard to be recognized early enough to prevent serious accidents that may lead even to road deaths. In this work, we propose a new drowsiness state detection system based on physiological signals and eye blinking. An experiment has been directed to justify the utility of the proposed approach. This system uses a smart video camera that takes drivers faces images and supervises the eye blink (open and close); also, it uses the Emotiv EPOC headset to acquire the electroencephalogram (EEG) signals. Eye detection is done by Viola and Jones technique, EEG. Finally, we have chosen the fuzzy logic techniques to classify the EEG signals and eye blinking detection to analyze the results.

Research paper thumbnail of Multidimensional Schema Evolution - Integrating New OLAP Requirements

International Conference on Enterprise Information Systems, 2006

Multidimensional databases are an effective support for OLAP processes. They improve the enterpri... more Multidimensional databases are an effective support for OLAP processes. They improve the enterprise decision-making. These databases evolve with the decision maker requirements evolution and, are sensitive to data source changes. In this paper, we are interested in the evolution of the data mart schema due to the raise of new OLAP needs. Our approach determines first, what functional data marts will be able to cover a new requirement, if any, and secondly, decides on a strategy of integration. This leads either to the alteration of an existing data mart schema or, to the creation of a new schema suitable for the new requirement.

Research paper thumbnail of The Multi-Agents Architecture for Emotion Recognition

International Journal of Software Innovation, 2014

The author's research focuses on the problem of Information Retrieval System (IRS) that integ... more The author's research focuses on the problem of Information Retrieval System (IRS) that integrates the human emotion recognition. This system must be able to recognize the degree of satisfaction of the user for the result found through its facial expression, its physiological state, its gestures and its voice. This paper is an algorithm for recognizing the emotional state of a user during a search session in order to issue the relevant documents that the user needs. The authors also present the architecture agent of the envisaged system and the organizational model.

Research paper thumbnail of Feast: face and emotion analysis system for smart tablets

Multimedia Tools and Applications, 2014

ABSTRACT Face and emotion recognition is still an open and very challenging problem. This paper p... more ABSTRACT Face and emotion recognition is still an open and very challenging problem. This paper presents a system FEAST which is an intelligent control system of Smart Tablets. It involves manipulating user sessions to adapt the working environment to his emotional state. First, a face detection followed by face and emotion recognition is performed, then a profile change is made basing on the obtained results. The face detection is based on skin color and geometric moments and face recognition is done by merging two features spaces, namely, Zernike moments and EAR-LBP. A feature selection technique reducing the parameter space size is applied. The same parameters are used for the emotion recognition.

Research paper thumbnail of Towards an intelligent information research system based on the human behavior: Recognition of user emotional state

ABSTRACT Our works deals with the problem of Information Retrieval System (IRS) that integrates t... more ABSTRACT Our works deals with the problem of Information Retrieval System (IRS) that integrates the human behaviour. This system must be able to recognize the degree of satisfaction of the user of the result found through its facial expression, its physiological state, its gestures and its voice. For this, we propose in this paper an algorithm for recognizing the emotional state of a user during a search session in order to issue the relevant documents that he needs. We present also, the architecture agent of the envisaged system.

Research paper thumbnail of Real-time affective learner profile analysis using an EMASPEL framework

Page 1. Real-time affective learner profile analysis using an EMASPEL framework Mohamed Neji, Moh... more Page 1. Real-time affective learner profile analysis using an EMASPEL framework Mohamed Neji, Mohamed Ben Ammar, Adel M. Alimi Research Group on Intelligent Machines University of Sfax, National school of engineers (ENIS), BP1173, Sfax, 3038, Tunisia. ...

Research paper thumbnail of Emotion recognition by analysis of EEG signals

13th International Conference on Hybrid Intelligent Systems (HIS 2013), 2013

ABSTRACT We propose in this paper an emotional recognition system based on physiological signals.... more ABSTRACT We propose in this paper an emotional recognition system based on physiological signals. We adopt the seven basic emotions that are: neutrality, joy, sadness, fear, anger, disgust and surprise. An experiment has been conducted to verify the feasibility of the proposed system. This experience has allowed us to acquire EEG signals and to create an emotional database. For this, we have used the Emotiv EPOC headset. Thereafter, we have chosen the fuzzy logic techniques to classify the EEG signals and to analyze the results.