Albert Ali Salah

Utrecht University | UU · Department of Information and Computing Sciences

The way the human body is depicted in classical and modern paintings is relevant for art historical analyses. Each artist has certain themes and concerns, resulting in different poses being used more heavily than others. In this paper, we propose a computer vision pipeline to analyse human pose and representations in paintings, which can be used fo...

The emergence of COVID-19 has had a global and profound impact, not only on society as a whole, but also on the lives of individuals. Various prevention measures were introduced around the world to limit the transmission of the disease, including face masks, mandates for social distancing and regular disinfection in public spaces, and the use of sc...

Advances in animal motion tracking and pose recognition have been a game changer in the study of animal behavior. Recently, an increasing number of works go ‘deeper’ than tracking, and address automated recognition of animals’ internal states such as emotions and pain with the aim of improving animal welfare, making this a timely moment for a syste...

The emergence of COVID-19 has had a global and profound impact, not only on society as a whole, but also on the lives of individuals. Various prevention measures were introduced around the world to limit the transmission of the disease, including face masks, mandates for social distancing and regular disinfection in public spaces, and the use of sc...

Pain is a serious and costly issue globally, but to be treated, it must first be detected. Vision transformers are a top-performing architecture in computer vision, with little research on their use for pain detection. In this paper, we propose the first fully-attentive automated pain detection pipeline that achieves state-of-the-art performance on...

The way the human body is depicted in classical and modern paintings is relevant for art historical analyses. Each artist has certain themes and concerns, resulting in different poses being used more heavily than others. In this paper, we propose a computer vision pipeline to analyse human pose and representations in paintings, which can be used fo...

Bipolar disorder is a mental health disorder that causes mood swings that range from depression to mania. Clinical diagnosis of bipolar disorder is based on patient interviews and reports obtained from the relatives of the patients. Subsequently, the diagnosis depends on the experience of the expert, and there is co-morbidity with other mental diso...

Dog owners are typically capable of recognizing behavioral cues that reveal subjective states of their dogs, such as pain. But automatic recognition of the pain state is very challenging. This paper proposes a novel video-based, two-stream deep neural network approach for this problem. We extract and preprocess body keypoints, and compute features...

The report illustrates the state of the art of the most successful AAL applications and functions based on audio and video data, namely (i) lifelogging and self-monitoring, (ii) remote monitoring of vital signs, (iii) emotional state recognition, (iv) food intake monitoring, activity and behaviour recognition, (v) activity and personal assistance,...

Advances in animal motion tracking and pose recognition have been a game changer in the study of animal behavior. Recently, an increasing number of works go 'deeper' than tracking, and address automated recognition of animals' internal states such as emotions and pain with the aim of improving animal welfare, making this a timely moment for a syste...

Inpatient violence is a common and severe problem within psychiatry. Knowing who might become violent can influence staffing levels and mitigate severity. Predictive machine learning models can assess each patient's likelihood of becoming violent based on clinical notes. Yet, while machine learning models benefit from having more data, data availab...

It is a matter of fact that Europe is facing more and more crucial challenges regarding health and social care due to the demographic change and the current economic context. The recent COVID-19 pandemic has stressed this situation even further, thus highlighting the need for taking action. Active and Assisted Living (AAL) technologies come as a vi...

Inpatient violence is a common and severe problem within psychiatry. Knowing who might become violent can influence staffing levels and mitigate severity. Predictive machine learning models can assess each patient’s likelihood of becoming violent based on clinical notes. Yet, while machine learning models benefit from having more data, data availab...

Bipolar disorder is a mental disorder that causes periods of manic and depressive episodes. In this work, we classify recordings from Bipolar Disorder corpus that contain 7 different tasks, into hypomania, mania, and remission classes using only speech features. We perform our experiments on splitted tasks from the interviews. Best results achieved...

This chapter discusses the key techniques in machine learning (ML) and their use in various urban computing (UC) scenarios. It introduces the main concepts and key techniques of ML, followed by relevant issues while designing any ML study. ML methods can adapt to dynamically changing environments, which is very important in UC, as cities are consta...

Recognition of pain in animals is essential for their welfare. However, since there is no verbal communication, this assessment depends solely on the ability of the observer to locate visible or audible signs of pain. The use of grimace scales is proven to be efficient in detecting the pain visually, but the assessment quality depends on the level...

Ambient assisted living (AAL) technologies are increasingly presented and sold as essential smart additions to daily life and home environments that will radically transform the healthcare and wellness markets of the future. An ethical approach and a thorough understanding of all ethics in surveillance/monitoring architectures are therefore pressin...

Ambient assisted living (AAL) technologies are increasingly presented and sold as essential smart additions to daily life and home environments that will radically transform the healthcare and wellness markets of the future. An ethical approach and a thorough understanding of all ethics in surveillance/monitoring architectures are therefore pressin...

Automatically verifying the identity of a person by means of biometrics is an important application in day-to-day activities such as accessing banking services and security control in airports. To increase the system reliability, several biometric devices are often used. Such a combined system is known as a multimodal biometric system. This paper r...

Many people experience a traumatic event during their lifetime. In some extraordinary situations, such as natural disasters, war, massacres, terrorism, or mass migration, the traumatic event is shared by a community and the effects go beyond those directly affected. Today, thanks to recorded interviews and testimonials, many archives and collection...

Multimodal interfaces offer ever-changing tasks and challenges for designers to accommodate newer technologies, and as these technologies become more accessible, newer application scenarios emerge. Prototype development and user evaluation are important steps in the creation of solutions to these challenges. Furthermore, playful interactions and ga...

Board games are fertile grounds for the display of social signals, and they provide insights into psychological indicators in multi-person interactions. In this work, we introduce a new dataset collected from four-player board game sessions, recorded via multiple cameras, and containing over 46 hours of visual material. The new MUMBAI dataset is ex...

The 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020) was held online between 16 and 20 November 2020. The IEEE conference series on Automatic Face and Gesture Recognition is the premier international forum for research in image and video-based face, gesture, and body movement recognition. The program chairs of...

Objective: We explore state of the art machine learning based tools for automatic facial and linguistic affect analysis to allow easier, faster, and more precise quantification and annotation of children’s verbal and non-verbal affective expressions in psychodynamic child psychotherapy. Method: The sample included 53 Turkish children: 41 with inter...

Introduction: The most prominent risk factor of Alzheimer's disease (AD) is aging. Aging also influences the physical appearance. Our clinical experience suggests that patients with AD may appear younger than their actual age. Based on this empirical observation, we set forth to test the hypothesis with human and computer-based estimation systems....

Acoustic and linguistic analysis for elderly emotion recognition is an under-studied and challenging research direction, but essential for the creation of digital assistants for the elderly, as well as unobtrusive telemonitoring of elderly in their residences for mental healthcare purposes. This paper presents our contribution to the INTERSPEECH 20...

Advances in human action recognition and interaction recognition enable the reliable execution of action classification tasks through machine learning algorithms. However, no systematic approach for developing such classifiers exists and since actions vary between domains, appropriate and usable datasets are uncommon. In this paper, we propose a re...

This paper describes how mobile phone data can support government and public health policymaking throughout the COVID-19 pandemic lifecycle, providing increased situational awareness, more accurate predictions, impact assessment of the policies and cause-and-effect inferences. It identifies key gaps and reasons why this kind of data is only scarcel...

This paper describes how mobile phone data can guide government and public health authorities in determining the best course of action to control the COVID-19 pandemic and in assessing the effectiveness of control measures such as physical distancing. It identifies key gaps and reasons why this kind of data is only scarcely used, although their val...

Paintings give us important clues about how males and females were perceived over centuries in the Western culture. In this article, we describe a system that allows scholars to automatically visualize how the clothing colors of male and female subjects changed over time. Our system analyzes a large database of paintings, locates portraits, automat...

Cross-language, cross-cultural emotion recognition and accurate prediction of affective disorders are two of the major challenges in affective computing today. In this work, we compare several systems for Detecting Depression with AI Sub-challenge (DDS) and Cross-cultural Emotion Sub-challenge (CES) that are published as part of the AudioVisual Emo...

Play therapy is an approach to psychotherapy where a child is engaging in play activities. Because of the strong affective component of play, it provides a natural setting to analyze feelings and coping strategies of the child. In this paper, we investigate an approach to track the affective state of a child during a play therapy session. We assume...

Leveraging call detail records for humanitarian analysis involves the collection and sharing of a large set of behavioral data, from hundreds of thousands of people. There is a risk that such data could be misused for surveillance and suppression, and there are strong criticisms that have been leveled at efforts involving call detail records. The D...

The Data for Refugees (D4R) Challenge resulted in many insights related to the movement patterns of the Syrian refugees within Turkey. In this chapter, we summarize some of the important findings, and suggest policy recommendations for the main areas of the challenge. These recommendations are sometimes broad suggestions, as the policy intervention...

The Data for Refugees (D4R) Challenge was a nonprofit challenge initiated to improve the conditions of the Syrian refugees in Turkey by providing a special database to scientific community for enabling research on urgent problems concerning refugees, including health, education, unemployment, safety, and social integration. The collected database w...

Many people experience a traumatic event during their lifetime. In some extraordinary situations, such as natural disasters, war, massacres, terrorism or mass migration, the traumatic event is shared by a community and the effects go beyond those directly affected. Today, thanks to recorded interviews and testimonials, many archives and collections...

Omnidirectional cameras cover more ground than perspective cameras, at the expense of resolution. Their comprehensive field of view makes omnidirectional cameras appealing for security and ambient intelligence applications. Person detection is usually a core part of such applications. Conventional methods fail for omnidirectional images due to diff...

This book constitutes the proceedings of the 21st International Conference on Speech and Computer, SPECOM 2019, held in Istanbul, Turkey, in August 2019. The 57 papers presented were carefully reviewed and selected from 86 submissions. The papers present current research in the area of computer speech processing including audio signal processing, a...

After the start of the Syrian Civil War in 2011–12, increasing numbers of civilians sought refuge in neighboring countries. By May 2017, Turkey had received over 3 million refugees — the largest r efugee population in the world. Some lived in government-run camps near the Syrian border, but many have moved to cities looking for work and better livi...

In the wild emotion recognition requires dealing with large variances in input signals, multiple sources of noise that will distract the learners, as well as difficult annotation and ground truth acquisition conditions. In this chapter, we briefly survey the latest developments in multimodal approaches for video-based emotion recognition in the wil...

Automatic analysis of job interview screening decisions is useful for establishing the nature of biases that may play a role in such decisions. In particular, assessment of apparent personality gives insights into the first impressions evoked by a candidate. Such analysis tools can be used for training purposes, if they can be configured to provide...

The Audio/Visual Emotion Challenge and Workshop (AVEC 2018) "Bipolar disorder, and cross-cultural affect recognition'' is the eighth competition event aimed at the comparison of multimedia processing and machine learning methods for automatic audiovisual health and emotion analysis, with all participants competing strictly under the same conditions...

The Data for Refugees (D4R) Challenge is a non-profit challenge initiated to improve the conditions of the Syrian refugees in Turkey by providing a special database to scientific community for enabling research on urgent problems concerning refugees, including health, education, unemployment, safety, and social integration. The collected database i...

Perceptual understanding of media content has many applications, including content-based retrieval, marketing, content optimization, psychological assessment, and affect-based learning. In this paper, we model audio visual features extracted from videos via machine learning approaches to estimate the affective responses of the viewers. We use the L...

On-line social platforms implement moderation mechanisms to filter out unwanted content and to take action against possible cases of verbal aggression and abuse, sexual harassment, and such. In this study, the authors investigate chat biometrics, the identification of users from their verbal behaviour on a social platform. The typical application s...

Explainability and interpretability are two critical aspects of decision support systems. Within computer vision, they are critical in certain tasks related to human behavior analysis such as in health care applications. Despite their importance, it is only recently that researchers are starting to explore these aspects. This paper provides an intr...

The purpose of the present study is to introduce a method for automatically extracting color distributions and main colors of paintings, as well as color schemes of people in paintings. By visualizing these over time for crossreferencing with historical data will reveal changes of how particular colors were used in a given time period and culture....

Visualization of text can be a useful exploration tool for looking at the corpus of a poet, especially when dealing with a prolific author with a large body of output over the years. In this work, we describe a flexible and extensible tool for analysing the corpus of a poet, and make a case study of Nˆazım Hikmet Ran. Since poetry has its own chall...

We describe an end-to-end system for explainable automatic job candidate screening from video CVs. In this application, audio, face and scene features are first computed from an input video CV, using rich feature sets. These multiple modalities are fed into modality-specific regressors to predict apparent personality traits and a variable that pred...

In this article, we present the first child emotional speech corpus in Russian, called “EmoChildRu”, collected from 3-7 years old children. The base corpus includes over 20K recordings (approx. 30 hours), collected from 120 children. Audio recordings are carried out in three controlled settings by creating different emotional states for children: p...

Ambient assisted living proposes to utilize technological solutions to sustain the well being of elderly people. In accordance with the vision of successful aging, we describe in this study an autonomous robotic exercise tutor for elderly people. The robot learns a set of physical exercises from a human demonstrator in an imitation framework, and p...

Multimodal recognition of affective states is a difficult problem, unless the recording conditions are carefully controlled. For recognition “in the wild”, large variances in face pose and illumination, cluttered backgrounds, occlusions, audio and video noise, as well as issues with subtle cues of expression are some of the issues to target. In thi...

Large scale social events that involve violence may have dramatic political, economic and social consequences. These events may result in higher crime rates, spreading of infectious diseases, economic crises, and even in migration phenomena (e.g., refugees across borders or internally displaced people). Hence, researchers have started using mobile...

In this paper the organisers present a brief overview of the 2nd International Workshop on Emotion Representations and Modelling for Companion Systems (ERM4CT). The ERM4CT 2016 Workshop is held in conjunction with the 18th ACM International Conference on Multimodal Interaction (ICMI 2016) taking place Tokyo, Japan. The ERM4CT is the follow-up of th...