Abdulmotaleb El Saddik

University of Ottawa · School of Electrical Engineering and Computer Science

Meta-learning approaches have recently achieved promising performance in multi-class incremental learning. However, meta-learners still suffer from catastrophic forgetting, i.e., they tend to forget the learned knowledge from the old tasks, when they focus on rapidly adapting to the new classes of the current task. To solve this problem, we propose...

Particulate matter smaller than 2.5 microns (PM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2.5</sub> ) is one of the main pollutants that has considerable detrimental effects on human health. Estimating its concentration levels with ground monitors is inefficient for several reasons. In this study...

A recently released cutting-edge AR device, Microsoft HoloLens, has attracted considerable attention with its advanced capabilities. In this article, we report the design and execution of a series of experiments to quantitatively evaluate HoloLens' performance in head localization, real environment reconstruction, spatial mapping, hologram visualiz...

To increase the quality of citizens' lives, we designed a personalized smart chair system to recognize sitting behaviors. The system can receive surface pressure data from the designed sensor and provide feedback for guiding the user towards proper sitting postures. We used a liquid state machine and a logistic regression classifier to construct a...

3D pose estimation is a challenging problem in computer vision. Most of the existing neural-network-based approaches address color or depth images through convolution networks (CNNs). In this paper, we study the task of 3D human pose estimation from depth images. Different from the existing CNN-based human pose estimation method, we propose a deep...

Microsoft Kinect sensor has been widely used in many applications since the launch of its first version. Recently, Microsoft released a new version of Kinect sensor with improved hardware. However, the accuracy assessment of the sensor remains to be answered. In this paper, we measure the depth accuracy of the newly released Kinect v2 depth sensor,...

Augmented reality (AR) technology is developing fast and provides users with new ways to interact with the real-world surrounding environment. Although the performance of holographic AR multimedia devices can be measured with traditional quality-of-service parameters, a quality-of-experience (QoE) model can better evaluate the device from the persp...

With the increase in health consciousness, noninvasive body monitoring has aroused interest among researchers. As one of the most important pieces of physiological information, researchers have remotely estimated the heart rate (HR) from facial videos in recent years. Although progress has been made over the past few years, there are still some lim...

In this paper, a Kinect-based distributed and real-time motion capture system is developed. A trigonometric method is applied to calculate the relative position of Kinect v2 sensors with a calibration wand and register the sensors' positions automatically. By combining results from multiple sensors with a nonlinear least square method, the accuracy...

Three-dimensional (3D) technologies have been developing rapidly recent years, and have influenced industrial, medical, cultural, and many other fields. In this paper, we introduce an automatic 3D human head scanning-printing system, which provides a complete pipeline to scan, reconstruct, select, and finally print out physical 3D human heads. To e...

In this paper, we develop an integrated markerless gait tracking system with three Kinect v2 sensors. A geometric principle-based trilateration method is proposed for optimizing the accuracy of the measured gait data. To tackle the data synchronization problem among the Kinect clients and the server, a synchronization mechanism based on NTP (Networ...

This letter presents a transducer network framework that supports the amalgamation of multiple transducers into single wireless nodes. This approach is aimed at decreasing energy consumption by reducing the number of wireless transceivers involved in such networks. To make wireless nodes easily reconfigurable, a plug and play mechanism is applied t...

Anemia is a worldwide health issue. To diagnose anemia, blood must be drawn to examine the hemoglobin level. The procedure is time-consuming and labor-intensive. The existing Artificial Intelligence (AI)-based anemia detection methods in literature have shortcomings, including, i) specially designed data collection device, ii) manual feature extrac...

Human bio-signal fusion is considered a critical technological solution that needs to be advanced to enable modern and secure digital health and well-being applications in the metaverse. To support such efforts, we propose a new data-driven digital twin (DT) system to fuse three human physiological bio-signals: heart rate (HR), breathing rate (BR),...

The new-generation information technology development enables Digital Twins to reshape the physical world into the virtual digital space and provide technical support for Metaverse construction. The Metaverse objects can be mesoscale or macro-micro-scales. Metaverse is a complex collection of both solid substances and liquid, gaseous, plasma, and o...

In person re-identification (Re-ID) , the data annotation cost of supervised learning, is huge and it cannot adapt well to complex situations. Therefore, compared with supervised deep learning methods, unsupervised methods are more in line with actual needs. In unsupervised learning, a key to solving Re-ID is to find a standard that can effectively...

The advances in Artificial Intelligence (AI) have led to technological advancements in a plethora of domains. Healthcare, education, and smart city services are now enriched with AI capabilities. These technological advancements would not have been realized without the assistance of fast, secure, and fault-tolerant communication media. Traditional...

In the digital era, extended reality (XR) is considered the next frontier. However, XR systems are computationally intensive, and they must be implemented within strict latency constraints. Thus, XR devices with finite computing resources are limited in terms of quality of experience (QoE) they can offer, particularly in the cases of big 3D data. T...

The current studies of Scene Graph Generation (SGG) focus on solving the long-tailed problem for generating unbiased scene graphs. However, most de-biasing methods overemphasize the tail predicates and underestimate head ones throughout training, thereby wrecking the representation ability of head predicate features. Furthermore, these impaired fea...

This exploratory study is the first to present an in vivo method to capture rich, longitudinal data on the prevalence and features of student-athletes’ smartphone usage and concurrent psychosocial outcomes. Ten competitive Canadian student-athletes were meticulously tracked through the collection of monthly self-report surveys and real-time smartph...

Due to the outbreak of Covid-19 pandemic, activities in most sectors- be it business, education or even healthcare- are taking place in an online rather than in an inline style, and as a result, Internet traffic has increased drastically. Recent studies have highlighted that internet traffic has grown by 70% to 300% since March 2020. According to a...

The increase in chronic diseases has affected the countries’ health system and economy. With the recent COVID-19 virus, humanity has experienced a great challenge, which has led to make efforts to detect it and prevent its spread. Hence, it is necessary to develop new solutions that are based on technology and low cost, to satisfy the citizens’ nee...

This dataset is used in https://ieeexplore.ieee.org/abstract/document/9681996). The dataset involves 27 volunteer subjects between 18-50 years old, monitored over one week from 20th June 2020 to 30th June 2020. Multimodal data were sensed using the sensor, app, and IoT technologies available on Redmi 8 Pro Android smartphone, Xiaomi Mi band 5, and...

Telehealth data during COVID-19

Digital twin (DT) has gained success in various industries, and it is now getting attention in the healthcare industry in the form of well-being digital twin (WDT). In this paper, we present an overview of WDT to understand its potential scope, architecture and impact. We then discuss the definition and the benefits of WDT. After that, we present t...

Sporting events generate a massive amount of traffic on social media with live moment-to-moment accounts as any given situation unfolds. The generated data are intensified by fans feelings, reactions, and subjective opinions towards what happens during the event, all of which are based on their individual points of view. Analyzing and summarizing t...

Visible-infrared person re-identification (VI-ReID) is a challenging task in computer vision, aiming at matching people across images from visible and infrared modalities. The widely used VI-ReID framework consists of a convolution neural backbone network that extracts the visual features, and a feature embedding network to project heterogeneous fe...

Challenges still exist in the task of object detection in remote sensing images with densely distributed objects due to large variation in scale and neglect of the relative position and correlation. To address these issues, a Correlation Learning Detector based on Transformer (CLT-Det) is proposed for detecting dense objects in remote sensing image...

The advances in Artificial Intelligence (AI) have led to technological advancements in a plethora of domains. Healthcare, education, and smart city services are now enriched with AI capabilities. These technological advancements would not have been realized without the assistance of fast, secure, and fault-tolerant communication media. Traditional...

Traffic events are one of the main causes of traffic accidents, leading to traffic event detection being a challenging research problem in traffic management and intelligent transportation systems (ITSs). The main gap in this task lies in how to extract and represent the valuable information from various kinds of traffic data. Considering the impor...

Diabetic retinopathy (DR) is one of the most common causes of vision loss in people who have diabetes for a prolonged period. Convolutional neural networks (CNNs) have become increasingly popular for computer-aided DR diagnosis using retinal fundus images. While these CNNs are highly reliable, their lack of sufficient explainability prevents them f...

Digital twin (DT) has gained success in various industries, and it is now getting attention in the healthcare industry in the form of well-being digital twin (WDT). In this paper, we present an overview of WDT to understand its potential scope, architecture and impact. We then discuss the definition and the benefits of WDT. After that, we present t...

The non-contact monitoring of vital signs, especially the Heart Rate (HR) and Breathing Rate (BR), using facial video is becoming increasingly important. Although, researchers have made considerable progress in the past few years, there are still some limitations to the technology, such as the lack of challenging datasets, the time consuming nature...

Security with biometrics has become popular with the increase use of technology and the availability of portable gadgets. Available commercial products include face recognition, fingerprints and other biometrics to grant access to authorized users. ECG as biometrics is a relatively new technology and has advantages over traditional biometrics. This...

Exercise is a prevailing topic in modern society as more people are pursuing a healthy lifestyle. Physical activities provide significant benefits to human well-being from the inside out. Human pose estimation, action recognition and repetitive counting fields developed rapidly in the past several years. However, few works combined them together to...

A Digital Twin (DT) is a digital replica of a living or non-living entity, called “real twin.” Data is collected from the real twin and analyzed using Artificial Intelligence (AI), which subsequently provides the real twin with valuable feedback. One of the most promising applications for humans is the DT for health and well-being [1]. Although the...

Emotion care for human well-being is important for all ages. In this paper, we propose an emotion care system based on big data analysis for autism disorder patient training, where emotion is detected in terms of facial expression. The expression can be captured through a camera as well as Internet of Things (IoT)-enabled devices. The system works...

Smart healthcare is a framework that utilizes technologies such as wearable devices, the Internet of Medical Things (IoMT), sophisticated machine learning algorithms, and wireless communication technology to seamlessly access health records, link individuals, resources, and organizations, and then effectively handle and react to health environment...

In order to flatten the curve and lower human-to-human transmission of COVID-19 pathogen, one of the critical suggestions by health professionals is to monitor COVID-19 virus status of each human dynamically which is not a pragmatic solution unless the COVID-19 positive, negative, or symptomatic subjects are identified and have a secure health cert...

The novel coronavirus SARS-CoV-2 that causes the disease COVID-19 has forced us to go into our homes and limit our physical interactions with others. Economies around the world have come to a halt, with non-essential businesses being forced to close in order to prevent further propagation of the virus. Developing countries are having more difficult...

With communications being shifted to online social networks (OSNs) as a result of travel and social restrictions during COVID-19 pandemic, the need has arisen for discovering emerging trends and concerns formed during the pandemic as well as understanding the corresponding online social behavior that reflects its offline settings. The online connec...

Smart cities are being developed to boost the wellness and quality of life of their citizens. To achieve this, we see an increase in the convergence of technologies, scientific knowledge and political will, and it is safe to say that in the next few years, there will be new societal trends and challenges in the fields of health, wellness, security,...

Unsupervised domain adaptation (UDA) for person re-identication (ReID) remains a challenging task, as the trained ReID system often fails to adapting to a new dataset. Due to the lack of supervision of real labels, the performance of the UDA models suffers from inefficient feature learning and inevitable pseudo label noise. In this work, we tackle...

Digital twins (DTs) technology has recently gained attention within the research community due to its potential to help build sustainable smart cities. However, there is a gap in the literature: currently no unified model for city services has been proposed that can guarantee interoperability across cities, capture each city’s unique characteristic...

Executive function and motor control deficits adversely affect gait performance with age, but the neural correlates underlying this interaction during stair climbing remains unclear. Twenty older adults (72.7 ± 6.9 years) completed single tasks: standing and responding to a response time task (SC), ascending or descending stairs (SMup, SMdown); and...

Cyber-Physical Systems (CPS) embed computation and communication capability into its core to regulate physical processes and seamlessly mediate between the cyber and the physical world for various control and monitoring tasks. Health CPS, a variant of CPS in the healthcare sector, acts as a health monitoring system to dynamically capture, process,...

Exertion games (exergames) pose interesting challenges in terms of user interaction techniques. Players are commonly unable to use traditional input devices such as mouse and keyboard, given the body movement requirements of this type of videogames. In this work we propose a hand gesture interface to direct actions in a target-shooting exertion gam...

Digital Twin technology has been rising in popularity thanks to the popularity of machine learning in the last decade. As the life expectancy of people around the world is increasing, so is the focus on physical activity to remain healthy especially in the current times where people are staying sedentary while in quarantine. This article aims to pr...

We propose an automatic, low-cost, large-scale, nonintrusive human need recognition framework that utilized a multi-layered psychological-based reference model and designed with different modules including data collection, preprocessing, feature extraction and contextualization module. The reference model comprises several classification and regres...

Internet of Things (IoT) has been the driving force for many smart city applications. The huge volume of IoT data generated from these applications require efficient processing to get the insight, which poses significant difficulty. Data mining and machine learning (DM) algorithms are used to minimize such difficulty. However, it is still very chal...

To increase the quality of citizens’ lives, we designed a personalized smart chair system to recognize sitting behaviors. The system can receive surface pressure data from the designed sensor and provide feedback for guiding the user towards proper sitting postures. We used a liquid state machine and a logistic regression classifier to construct a...

Visible–infrared cross-modality person re-identification is a realistic problem of person re-identification. Under poor illumination scenario, general methods of visible–visible person re-identification can not solve the problem well. If we directly compare the visible images of pedestrians captured under dark lighting with the visible images of pe...

In the past decade, auditory and visual multimedia have reached an advanced quality level which is characteristically referred to as high definition (HD) and beyond. On the contrary, technical solutions addressing the sense of touch, which are typically referred to as haptic technology, have not yet received the same level of attention and evolutio...

Human vital signs are essential information that are closely related to both physical cardiac assessments and psychological emotion studies. One of the most important data is the heart rate, which is closely connected to the clinical state of the human body. Modern image processing technologies, such as Remote Photoplethysmography (rPPG), have enab...

The Lactate threshold (LT) has gained special attention in the sport world and is considered one of the potential indicators to evaluate individual performance in different sports. Traditionally, measuring LT requires frequent collection of blood samples from individuals under specific spatiotemporal conditions. This procedure causes discomfort to...

Governments and municipalities need to understand their citizens’ psychological needs in critical times and dangerous situations. COVID-19 brings lots of challenges to deal with. We propose NeedFull, an interactive and scalable tweet analysis platform, to help governments and municipalities to understand residents’ real psychological needs during t...

Supervised depth prediction and optical flow estimation have achieved promising performance due to the advanced deep network architectures. Since the ground truths are difficult to be collected, many recent works try to learn the depth and flow in an unsupervised manner. However, existing methods only use features from convolutional layers or a sim...

The papers in this special section focus on the topic of urban multimedia computing. Presents emerging methods in multimedia computing for urban analysis and applications. Urban computing is a process of acquisition, integration, analysis, and understanding of the urban data generated from various sources, e.g., sensors, devices, and social media,...

The use of the digital twin has been quickly adopted in industry in recent years and continues to gain momentum. The recent redefinition of the digital twin from the digital replica of a physical asset to the replica of a living or nonliving entity has increased its potential. The digital twin not only disrupts industrial processes, but also expand...

3D pose estimation is a challenging problem in computer vision. Most of the existing neural-network-based approaches address color or depth images through convolution networks (CNNs). In this paper, we study the task of 3D human pose estimation from depth images. Different from the existing CNN-based human pose estimation method, we propose a deep...

Automatic detection of pavement crack is an important task for conducting road maintenance. However, as an important part of the intelligent transportation system, automatic pavement crack detection is challenging due to the poor continuity of cracks, the different width of cracks, and the low contrast between cracks and the surrounding pavement. T...

Recently, the focus on sentiment analysis has been domain dependent even though the expressions used by the public are unsophisticatedly familiar regardless of the topics or domains. Online social media (OSNs) has been a daily venue for informal conversational contents from various domains ranging from sports and cooking to politics and human right...