Papers by Abdunnaser Diaf
Lecture Notes in Computer Science, 2010
This paper proposes a novel and robust appearance-based method for human motion recognition based... more This paper proposes a novel and robust appearance-based method for human motion recognition based on the eigenspace technique. This method has three main advantages over the existing appearance-based methods. First, the Linear Discriminant Analysis (LDA) is used for dimensionality reduction and eigenspace generation, while preserving maximum separability between classes. Second, by combining a novel centering technique with an incremental procedure,
The author has granted a non exclusive license allowing Library and Archives Canada to reproduce,... more The author has granted a non exclusive license allowing Library and Archives Canada to reproduce, publish, archive, preserve, conserve, communicate to the public by telecommunication or on the Internet, loan, distribute and sell theses worldwide, for commercial or non commercial purposes, in microform, paper, electronic and/or any other formats. AVIS: L'auteur a accordé une licence non exclusive permettant à la Bibliothèque et Archives Canada de reproduire, publier, archiver, sauvegarder, conserver, transmettre au public par télécommunication ou par l'Internet, prêter, distribuer et vendre des thèses partout dans le monde, à des fins commerciales ou autres, sur support microforme, papier, électronique et/ou autres formats. V I Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 6 Im p lem en tin g an 0 .
Bubakeur Boufama and Dr. Rachid Benlamri. They gave their best in providing me with help, guidanc... more Bubakeur Boufama and Dr. Rachid Benlamri. They gave their best in providing me with help, guidance, and a stimulating and relaxed environment throughout the years of my studies. The discussions that I had with Boufama and Benlamri helped me having and developing many ideas in this thesis. However, their support was much more than just scientific. I gratefully acknowledge the valuable financial support from my beloved country, Libya, via the Ministry of Higher Education and Scientific Research for the period of Fall-2007 to Summer-2011 without which this work would not have been possible. My greatest thanks to my wife Sana for her understanding, love, support, and encouragement during the past few years without whom I would most certainly be lost. Last but not least two people I will certainly never forget: All my love to my parents, Abdulhamid and Njaima who dedicated their lives, health, and wealth "just as scented candles" for nothing but to see me and my siblings prosperous and healthy.
Communications in Computer and Information Science, 2012
Kernel-based methods have gained great attention by researchers in the field of pattern recogniti... more Kernel-based methods have gained great attention by researchers in the field of pattern recognition and statistical machine learning. They are the most nominated algorithms whenever a non-linear classification model is required. Human activity recognition has also been highlighted by researchers in the area of computer vision. This focusing has been triggered by the interest in many applications, such as, activity recognition in surveillance systems, robotics, wireless interfaces and interactive environments. It has been observed that the literature lacks the use of the kernel technique in the context of human activity recognition. In this context, this paper introduces a non-linear eigenvector-based recognition model that is built upon the idea of the kernel technique. The paper gives a practical study of using the kernel technique showing how much crucial choosing the right kernel function is, for the success of the linear discrimination in the feature space. The rich implementation results provided in this paper were obtained by applying the model on two of the most common used benchmark datasets in the field of human activity recognition, KTH and Weizmann.
Canadian Conference on Electrical and Computer Engineering, 2005., 2005
Several data-link control (DLC) protocol procedures have been proposed in order to provide reliab... more Several data-link control (DLC) protocol procedures have been proposed in order to provide reliable data transmission over powerless radio links. However, many QoS issues still need to be achieved such as balance between cell transfer delay (CTD) and cell loss rate (CLR), absence of cell delay variation (CDV), and network traffic utilization. The main problem with wireless ATM is how
Lecture Notes in Computer Science, 2012
ABSTRACT This paper proposes a robust appearance-based method for recognizing directed human acti... more ABSTRACT This paper proposes a robust appearance-based method for recognizing directed human activities with scale variation based on a compound eigenspace. The method addresses two main issues associated with activity recognition when a human is moving away from or closer to the cameras. The first issue is the variation in human silhouette sizes as a result of object-camera distance changes. The second is the insufficient information of shape and speed of the limbs due to self occlusions. An eigenvector-based linear algorithm is employed for dimensionality reduction and activity recognition here. In addition to the conventional data available in each video frame, our method extracts two more pieces of information that are used to control the recognition process. In particular, the use of a compound eigenspace, controlled by the silhouette's relative speed and linear displacement vector, has clearly improved the recognition. The method has been trained and tested using the four scenarios of the KTH dataset, which contains hundreds of videos partitioned into six human activities.
Lecture Notes in Computer Science, 2010
Support Vector Machine (SVM) is a powerful classification methodology where the Support Vectors (... more Support Vector Machine (SVM) is a powerful classification methodology where the Support Vectors (SVs) fully describe the decision surface by incorporating local information. On the other hand, Nonparametric Discriminant Analysis (NDA) is an improvement over the more general Linear Discriminant Analysis (LDA) where the normality assumption from LDA is relaxed. NDA is also based on detecting the dominant normal directions to the decision surface. This paper introduces a novel SVM + NDA model which combines these two methods. This can be viewed as an extension to the SVM by incorporating some partially global information about the data, especially, discriminatory information in the normal direction to the decision boundary. This can also be considered as an extension to the NDA where the support vectors improve the choice of κ-nearest neighbors (κ−NN's) on the decision boundary by incorporating local information. Since our model is an extension to both SVM and NDA, it can deal with heteroscedastic and non-normal data. It also avoids the small sample size problem. Moreover, this model can be reduced to the classical SVM model so that the existing SVM programs can be used for easy implementation. An extensive comparison of the SVM + NDA to the LDA, SVM, NDA and the combined SVM and LDA, performed on artificial and real data sets, has shown the advantages and superiority of our proposed model. In particular, the experiments on face recognition have clearly shown a significant improvement of SVM + NDA over the other methods, especially, SVM and NDA.
2008 IEEE International Conference on Electro/Information Technology, 2008
Abstract As intelligent systems are being applied to increasingly larger, open and more complex p... more Abstract As intelligent systems are being applied to increasingly larger, open and more complex problem domains. These domains demand a systematic approach to handle the complexity in knowledge engineering. The needs include modularity in representation, ...
Pattern Recognition Letters, 2013
Kernel mapping has attracted a great deal of attention from researchers in the field of pattern r... more Kernel mapping has attracted a great deal of attention from researchers in the field of pattern recognition and statistical machine learning. Kernel-based approaches are the better choice whenever a non-linear classification model is needed. This paper proposes a nonlinear classification approach based on the non-parametric version of Fisher's discriminant analysis. This technique can efficiently find a nonparametric kernel representation where linear discriminants perform better. Data classification is achieved by integrating the linear version of the nonparametric Fisher's discriminant analysis with the kernel mapping. Based on the kernel trick, we provide a new formulation for Fisher's criterion, defined solely in terms of the inner dot-product of the original input data. The obtained experimental results have demonstrated the competitiveness of our approach compared to major state of the art approaches.
2010 Fifth International Conference on Digital Information Management (ICDIM), 2010
ABSTRACT This paper describes a new robust appearance-based method for representing and recognizi... more ABSTRACT This paper describes a new robust appearance-based method for representing and recognizing human behaviours using the eigenspace technique. This method has three main advantages over the existing appearance-based methods. First, the centering of the human-body blob, in each background-subtracted video frame, together with the use of an incremental procedure for compression, have made the extraction of the motion features limited to the smallest possible area in the image. Second, a learning strategy based on the eigen-space technique is employed for dimensionality reduction using the Linear Discriminant Analysis algorithm (LDA), while providing maximum separability between classes. Third, data retrieving has been greatly enhanced by using a directed acyclic graph (DAG) structure based on the Euclidean distance between projected data. The system has been tested using a large number of training motion videos partitioned into 6 human behaviours (boxing, hand-clapping, hand-waving, jogging, running, and walking) captured for 25 different persons in 2 different scenarios (indoor and outdoor). The experimental results are very good, showing a high performance level of the proposed method.
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Papers by Abdunnaser Diaf