
Philipp WernerOtto-von-Guericke University Magdeburg | OvGU · Institute for Information Technology and Communications
Philipp Werner
Dipl.-Ing.-Inf.
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71
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2,319
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Publications
Publications (71)
This study focuses on improving healthcare quality by introducing an automated system that continuously monitors patient pain intensity. The system analyzes the Electrodermal Activity (EDA) sensor modality modality, compares the results obtained from both EDA and facial expressions modalities, and late fuses EDA and facial expressions modalities. T...
The selection of a suitable region of interest (ROI) is of great importance in camera-based vital signs estimation, as it represents the first step in the processing pipeline. Since all further processing relies on the quality of the signal extracted from the ROI, the tracking of this area is decisive for the performance of the overall algorithm. T...
Pain is a reliable indicator of health issues; it affects patients’ quality of life when not well managed. The current methods in the clinical application undergo biases and errors; moreover, such methods do not facilitate continuous pain monitoring. For this purpose, the recent methodologies in automatic pain assessment were introduced, which demo...
Automatic systems enable continuous monitoring of patients' pain intensity as shown in prior studies. Facial expression and physiological data such as electrodermal activity (EDA) are very informative for pain recognition. The features extracted from EDA indicate the stress and anxiety caused by different levels of pain. In this paper, we investiga...
Face and person detection are important tasks in computer vision, as they represent the first component in many recognition systems, such as face recognition, facial expression analysis, body pose estimation, face attribute detection, or human action recognition. Thereby, their detection rate and runtime are crucial for the performance of the overa...
Vision-based 3D human pose estimation approaches are typically evaluated on datasets that are limited in diversity regarding many factors, e.g., subjects, poses, cameras, and lighting. However, for real-life applications, it would be desirable to create systems that work under arbitrary conditions (“in-the-wild”). To advance towards this goal, we i...
Prior work on automated methods demonstrated that it is possible to recognize pain intensity from frontal faces in videos, while there is an assumption that humans are very adept at this task compared to machines. In this paper, we investigate whether such an assumption is correct by comparing the results achieved by two human observers with the re...
We address the problem of facial expression analysis. The proposed approach predicts both basic emotion and valence/arousal values as a continuous measure for the emotional state. Experimental results including cross-database evaluation on the AffectNet, Aff-Wild, and AFEW dataset shows that our approach predicts emotion categories and valence/arou...
In computer vision, occlusions are mainly known as a challenge to cope with. For instance, partial occlusions of the face may lower the performance of facial expression recognition systems. However, when incorporated into the training, occlusions can be also helpful in improving the overall performance. In this paper, we propose and evaluate occlus...
Automatic understanding of facial behavior is hampered by factors such as occlusion, illumination, non-frontal head pose, low image resolution, or limitations in labeled training data. The EmotioNet 2020 Challenge addresses these issues through a competition on recognizing facial action units on in-the-wild data. We propose to combine multi-task an...
Background
In patients with limited communication skills, the use of conventional scales or external assessment is only possible to a limited extent or not at all. Multimodal pain recognition based on artificial intelligence (AI) algorithms could be a solution.Objective
Overview of the methods of automated multimodal pain measurement and their reco...
Background
The objective recording of subjectively experienced pain is a problem that has not been sufficiently solved to date. In recent years, data sets have been created to train artificial intelligence algorithms to recognize patterns of pain intensity. The multimodal recognition of pain with machine learning could provide a way to reduce an ov...
We address the problem of emotional state detection from facial expressions. Our proposed approach simultaneously detects faces and predicts both discrete emotion categories and continuous valence/arousal values from raw input images. We train and evaluate our approach on 3 different datasets, compare our approach to other state-of-the-art approach...
Pain is a complex phenomenon, involving sensory and emotional experience, that is often poorly understood, especially in infants, anesthetized patients, and others who cannot speak. Technology supporting pain assessment has the potential to help reduce suffering; however, advances are needed before it can be adopted clinically. This survey paper as...
Automatic pain recognition has great potential to improve pain management. In this work, we investigate multi-modality in pain recognition in two regards. First, we compare and combine multiple sensor modalities, which capture both behavioral and physiological pain responses. Second, we compare and distinguish the heat and the electrical pain stimu...
Current face detection concentrates on detecting tiny faces and severely occluded faces. Face analysis methods, however, require a good localization and would benefit greatly from some rotation information. We propose to predict a face direction vector (FDV), which provides the face size and orientation and can be learned by a common object detecti...
In this paper, we propose two simple yet effective methods to estimate facial attributes in unconstrained images. We use a straight forward and fast face alignment technique for preprocessing and estimate the face attributes using MobileNetV2 and Nasnet-Mobile, two lightweight CNN (Convolutional Neural Network) architectures. Both architectures per...
So far, all studies investigating the facial expression of pain have validated methods on the same database, whereas the cross-database performance is less considered. This may be due to poor performance of well-trained models on other databases. In this paper, we propose two distinct methods to classify based on the temporal information. To explor...
Experimental economic laboratories run many studies to test theoretical predictions with actual human behaviour, including public goods games. With this experiment, participants in a group have the option to invest money in a public account or to keep it. All the invested money is multiplied and then evenly distributed. This structure incentivizes...
Facial expression analysis is challenged by the numerous degrees of freedom regarding head pose, identity, illumination, occlusions, and the expressions itself. It currently seems hardly possible to densely cover this enormous space with data for training a universal well-performing expression recognition system. In this paper we address the sub-ch...
Facial expression analysis is challenged by the numerous degrees of freedom regarding head pose, identity, illumination, occlusions, and the expressions itself. It currently seems hardly possible to densely cover this enormous space with data for training a universal well-performing expression recognition system. In this paper we address the sub-ch...
Facial expression analysis is challenged by the numerous degrees of freedom regarding head pose, identity, illumination, occlusions, and the expressions itself. It currently seems hardly possible to densely cover this enormous space with data for training a universal well-performing expression recognition system. In this paper we address the sub-ch...
https://www.jove.com/video/59057/multi-modal-signals-for-analyzing-pain-responses-to-thermal
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The assessment of pain relies mostly on methods that require a person to communicate. However, for people with cognitive and verbal impairments, existing methods are not sufficient as they lack reliability and validity. To approach this problem, recen...
Objective:
Public databases are important for evaluating and comparing different methods and algorithms for camera based heart rate estimation. Because uncompressed video requires huge file sizes, a need for compression algorithms exists to store and share video data. Due to the optimization of modern video codecs for human perception, video compr...
The contact free camera-based estimation of human vital signs is more comfortable than the classical contact-based methods. Current methods suffer in realistic environments from e.g. occlusions by hair or glasses. Several approaches use complex methods to extract the pulse signals from the skin, but use basic geometric defined regions of the face,...
Random Tree Walkers (RTW) are a well-established method for human pose estimation, because they deliver state-of-the-art performance at low computational cost. As the forests capabilities for generalization are limited, the algorithm fails to estimate unlearned poses very quickly. The proposed method pushes this limitation by combining the RTW with...
Pain assessment can benefit from observation of pain behaviors, such as guarding or facial expression, and observational pain scales are widely used in clinical practice with nonverbal patients. However, little is known about head movements and postures in the context of pain. In this regard, we analyze videos of three publically available datasets...
This is the head pose data analysed in the paper "Head movements and postures as pain behavior" written by Philipp Werner, Ayoub Al-Hamadi, Kerstin Limbrecht-Ecklundt, Steffen Walter, and Harald C. Traue, DOI 10.1371/journal.pone.0192767. If you use it in some way, please cite the paper.
The ZIP file contains MAT files including head pose data of...
Automatic facial action unit intensity estimation can be useful for various applications in affective computing. In this paper, we apply random regression forests for this task and propose modifications that improve predictive performance compared to the original random forest. Further, we introduce a way to estimate and visualize the relevance of...
To develop automatic pain monitoring systems, we need a deep understanding of pain expression and its influencing factors and we need datasets with high-quality labels. This work analyzes the variation of facial activity with pain stimulus intensity and among subjects. We propose two distinct methods to assess facial expressiveness and apply them o...
Head pose estimation can help in understanding human behavior or to improve head pose invariance in various face analysis applications. Ready-to-use pose estimators are available with several facial landmark trackers, but their accuracy is commonly unknown. Following the goal to find the best landmark based pose estimator, we introduce a new databa...
In this work, a method is presented for the continuous estimation of pain intensity based on fusion of bio-physiological and video features. Furthermore, a method is proposed for the adaptation of the system to unknown test persons based on unlabeled data. First, an analysis is presented that shows which modalities and feature sets are suited best...
Video based heart rate estimation has several advantages compared to the classical method. Current approaches use long time windows (30sec) to calculate heart rates, which results in high latency and is a big disadvantage for a practical use. To overcome this constraint, we propose a low latency approach
for continuous frame based heart rate estima...
The precondition of productive data mining is having an efficient database to work on. The BioVid Emo DB is a multimodal database recorded for the purpose of analyzing human affective states and data mining related to emotion. Psychophysiological signals such as Skin Conductance Level, Electrocardiogram, Trapezius Electromyogram and also 4 video si...
Die kontaktfreie, kamerabasierte Messung von Vitalparameter des Menschen ist komfortabler als klassische kontaktbasierte Methoden. Aktuelle Verfahren haben jedoch noch Probleme in realistischen Anwendungsszenarien, z.B. bei Verdeckungen durch Haare oder Brillen. Zur Zeit werden zur Extraktion der nötigen Farbsignale geometrisch festgelegte Regionen...
Herzrate, Atmung und Herzratenvariabilität sind wichtige Vitalparameter des
Menschen, deren Messung in Echtzeit von großer medizinischer Bedeutung ist. Mo-
mentan vertriebene Geräte zur Messung dieser Parameter verwenden ausschließlich
kontaktbasierte Messmethoden. Diese sind mit einigen Nachteilen verbunden. Vor-
gestellt wird eine kontaktfreien...
Background
The monitoring of facial expressions to assess pain intensity provides a way to determine the need for pain medication in patients who are not able to do so verbally.
Objectives
In this study two methods for facial expression analysis – Facial Action Coding System (FACS) and electromyography (EMG) of the zygomaticus muscle and corrugator...
Pain is a primary symptom in medicine, and accurate assessment is needed for proper treatment. However, today’s pain assessment methods are not sufficiently valid and reliable in many cases. Automatic recognition systems may contribute to overcome this problem by facilitating objective and continuous assessment. In this article we propose a novel f...
The precondition of productive data mining is
having an efficient database to work on. The BioVid Emo DB is
a multimodal database recorded for the purpose of analyzing
human affective states and data mining related to emotion.
Psychophysiological signals such as Skin Conductance Level,
Electrocardiogram, Trapezius Electromyogram and also 4
video si...
Background:
The clinically used methods of pain diagnosis do not allow for objective and robust measurement, and physicians must rely on the patient's report on the pain sensation. Verbal scales, visual analog scales (VAS) or numeric rating scales (NRS) count among the most common tools, which are restricted to patients with normal mental abilitie...
In this work, a method is presented for the continuous estimation of pain intensity based on fusion of bio-physiological and video features. The focus of the paper is to analyse which modalities and feature sets are suited best for the task of recognizing pain levels in a person-independent setting. A large set of features is extracted from the ava...
Automatic Action Unit (AU) intensity estimation is a key problem in facial expression analysis. But limited research attention has been paid to the inherent class imbalance, which usually leads to suboptimal performance. To handle the imbalance, we propose (1) a novel multiclass under-sampling method and (2) its use in an ensemble. We compare our a...
During the last years KinectFusion and related algorithms have facilitated significant advances in real-time simultaneous localization and mapping (SLAM) with depth-sensing cameras. Nearly all of these algorithms represent the observed area with the truncated signed distance function (TSDF). The reconstruction accuracy achievable with the represent...
In this work, multi-modal fusion of video and biopotential signals is used to recognize pain in a person-independent scenario. For this purpose, participants were subjected to painful heat stimuli under controlled conditions. Subsequently, a multitude of features have been extracted from the available modalities. Experimental validation suggests th...
The objective measurement of subjective, multi-dimensionally experienced pain is a problem for which there has not been an adequate solution. Although verbal methods (e.g., pain scales and questionnaires) are commonly used to measure clinical pain, they tend to lack objectivity, reliability, or validity when applied to mentally impaired individuals...
Real-time 3D reconstruction is a hot topic in current research. Several popular approaches are based on the truncated signed distance function (TSDF), a volumetric scene representation that allows for integration of multiple depth images taken from different viewpoints. Aiming at a deeper understanding of TSDF we discuss its parameters, conduct exp...
Non-contact measurement of the heart rate is more comfortable than classical methods and can facilitate new applications. However, current approaches are very susceptible to motion. Aiming at overcoming this limitation, we propose a new, more robust approach to estimate the heart rate from a videotaped face. It features non-planar motion compensati...
How much does it hurt? Accurate assessment of pain is very important for selecting the right treatment, however current methods are not sufficiently valid and reliable in many cases. Automatic pain monitoring may help by providing an objective and continuous assessment. In this paper we propose an automatic pain recognition system combining informa...
Together with classification of facial expressions, the rating of their intensities is of major interest. Classical supervised learning techniques require labeling of the intensities, which is labor intensive and requires expert knowledge, but nevertheless is not guaranteed to be objective. We propose a new approach to learn an intensity rating fun...
Background / Purpose:
This work focuses on automatic pain recognition.
Main conclusion:
We found specific features regarding the pain levels.
Since its release in late 2010 the Microsoft Kinect depth sensor has boosted real time gesture recognition and new man-machine interaction endeavors in the computer vision community. Based on depth image data, in this paper we propose an accurate, fast and robust face pose estimation approach, which for example can be of interest for user behavior...
Pain is what the patient says it is. But what about these who cannot utter? Automatic pain monitoring opens up prospects for better treatment, but accurate assessment of pain is challenging due to the subjective nature of pain. To facilitate advances, we contribute a new dataset, the BioVid Heat Pain Database which contains videos and physiological...
The objective measurement of subjective, multi-dimensionally experienced pain is still a problem that has yet to be adequately solved. Though verbal methods (i.e., pain scales, questionnaires) and visual analogue scales are commonly used for measuring clinical pain, they tend to lack in reliability or validity when applied to mentally impaired indi...
Eine Middleware kann die Entwicklung von verteilten Systemen deutlich vereinfachen, insbesondere bei komplexen und heterogenen Systemen. Für verteilte Systeme mit harten Echtzeitanforderungenist eine zeitlich vorhersagbare Kommunikation unverzichtbar, so dass die Nutzung der gemeinsam genutzten Kommunikationsressourcen geplant werden muss. Diese Ar...
The BioVid Heat Pain Database was collected in a study with 90 participants who were subjected to experimentally induced heat pain stimuli in four intensities. It includes video and biomedical signals (EMG, ECG, EMG).
NEW WEBSITE: http://www.iikt.ovgu.de/BioVid
Automatic pain recognition can improve medical treatment, especially when the patient is not able to utter on his pain experience. Facial expressions with their intensities and dynamics contain valuable information for recognising pain. We propose a concept for distinguishing facial expressions of pain from others and assessing the pain expression...
Transferring datagrams is essential for a lot of tasks. If the data does not fit into one network packet, fragmentation is needed. We propose a fragmentation protocol that adapts to different MTUs and to the datagram size, ensuring efficient bandwidth utilization. The protocol is extensible to allow tailoring to network and application demands. Thu...
Questions
Questions (5)
There are many observation based pain scales. Which are the best regarding validity, reliability and responsiveness? Do you know independent literature that compares scales? Do you have own experiences?
I know that many scales are intended for specific groups of patients. I am not interested in any specific group, respectively I am interested in all patients. Thanks for your answers.
Author lists in IEEE journals are crowded with membership information, but I do not see why.
If I submit a manuscript, is there any benefit from being a member?
I am looking for all you know, just for comparison. I am not looking for methods, but for ready-to-use software which includes the trained models.
What I know so far:
- IntraFace: http://www.humansensing.cs.cmu.edu/intraface/
- Chehra: https://sites.google.com/site/chehrahome/home
- Robust Discriminative Response Map Fitting: http://ibug.doc.ic.ac.uk/resources/drmf-matlab-code-cvpr-2013/
- flandmark: http://cmp.felk.cvut.cz/~uricamic/flandmark/
- Face Alignment at 3000 (reimplementation): https://github.com/jwyang/face-alignment
I want to compare different facial expression recognition approaches on a (not yet) publically available dataset.
For this purpose I need at least one software that I can apply on my dataset videos out-of-the-box. A software based on a state-of-the-art method would be perfect. I also would prefer software that is free, at least for non-commercial research purposes.
I am not looking for methods, but for ready-to-use software including the trained recognition models.
Update: I do not need a fancy GUI or visualization, a simple command line application which reads an video file and writes a text file with FACS scores for each of the frames would be most helpful.
I have bad experience with some journals waiting for reviews for many months. In future I want to avoid that by selecting a journal with a fast review process.
I already found, that most of the Elsevier Journals provide statistics about review time. Geat. But do you know other publishers who also provide that information?
Or do you no websites which collect such statistics about journals? I think if the publisher do not publish that, the scientific community should gather that information.
It would be a nice additional feature for ResearchGate if we could annotate the journal publications with time-to-review and time-to-publication and search for journals based on the mean of that.
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