Changes In Facial Expression Research Articles

Blend Shape Interpolation and FACS for Realistic Avatar

The quest of developing realistic facial animation is ever-growing. The emergence of sophisticated algorithms, new graphical user interfaces, laser scans and advanced 3D tools imparted further impetus towards the rapid advancement of complex virtual human facial model. Face-to-face communication being the most natural way of human interaction, the facial animation systems became more attractive in the information technology era for sundry applications. The production of computer-animated movies using synthetic actors are still challenging issues. Proposed facial expression carries the signature of happiness, sadness, angry or cheerful, etc. The mood of a particular person in the midst of a large group can immediately be identified via very subtle changes in facial expressions. Facial expressions being very complex as well as important nonverbal communication channel are tricky to synthesize realistically using computer graphics. Computer synthesis of practical facial expressions must deal with the geometric representation of the human face and the control of the facial animation. We developed a new approach by integrating blend shape interpolation (BSI) and facial action coding system (FACS) to create a realistic and expressive computer facial animation design. The BSI is used to generate the natural face while the FACS is employed to reflect the exact facial muscle movements for four basic natural emotional expressions such as angry, happy, sad and fear with high fidelity. The results in perceiving the realistic facial expression for virtual human emotions based on facial skin color and texture may contribute towards the development of virtual reality and game environment of computer aided graphics animation systems. Realistic facial expressions of avatar.

Face recognition via optimized features fusion

Face recognition has received considerable attention in the field of computer vision and pattern recognition. The important applications of face recognition include but are not limited to Airport security, card security in ATM's, visa processing and the passport verification. Although there has been rigorous research in this area for almost a decade, the scientists have not been able to provide and agree to a standard for obtaining the salient information in facial images utilizing feature's categories. In this article, we have presented an approach where features are collected containing local and global face information i.e. geometric and appearance-based features. These features are fused, resulting in an increase in the face-recognition accuracy. First, the global features are obtained by utilizing Discrete Cosine Transform and Local facial features via Local Binary Pattern. In the next stage, both local and global features are combined using the concatenation method resulting in an increase in features. To reduce the data dimensions, Particle Swarm Optimization PSO along with Genetic Algorithm GA is applied to eliminate the redundant features that provide the optimized feature sets. We also provide empirical results of our proposed system. The system has been evaluated using ORL and Labeled Faces in the Wild LFW face databases. We have been able to obtain a promising 98% accuracy rate by using PSO-GA based optimized features albeit the reduced number of features. Features' fusion enables proposed system to be robust to variations like facial expression change, illumination effects and occlusions.

A Case of Special Complication following a Large Amount of Polyacrylamide Hydrogel Injected into the Epicranial Aponeurosis: Leukocytopenia.

Polyacrylamide hydrogel (PAAG) has been used as an injectable filler for soft tissue augmentation of different body parts, such as the face, breasts, and penis. However, this is the first report of leukocytopenia after injection of a large amount of PAAG in the epicranial aponeurosis. After receiving PAAG injection for craniofacial contouring, the female patient described herein experienced recurrent swelling, temporal pain (particularly with changes in ambient temperature and facial expression), and ultimately leukocytopenia due to widespread migration of the injected PAAG. We removed most of the PAAG from the affected tissues and the leukocytopenia disappeared 1 year after the operation. Based on this case, we hypothesize that injection of a large amount of PAAG into tissues that have ample blood supply, such as the epicranial aponeurosis, may induce leukocytopenia.

Contos infantojuvenis: uma prática lúdica de humanização para crianças hospitalizadas

Objective: to understand the reactions of hospitalized children and their families as they listen to children's stories during the activities of the research and extension project: Children’s and Juvenile Tales: an interface with the humanization of care in hospital. Method: this is a descriptive and qualitative study which used the observational method. Twelve children in hospital and their families participated in the study. Data were collected from participant observation and field record and then analyzed, giving rise to three categories. Results: there was evidence that children have different reactions while listening to the stories, such as changes in mood, body language and facial expressions. Furthermore, it was noticed that the hospitalized child’s family appreciates this playful practice as a moment of joy and enthusiasm. Conclusions: the study reveals the need for playful practices that humanize the pediatric environment and assist the child and their family in the hospitalization.

Recognition of facial actions and their temporal segments based on duration models

Being able to automatically analyze finegrained changes in facial expression into action units (AUs), of the Facial Action Coding System (FACS), and their temporal models (i.e., sequences of temporal phases, neutral, onset, apex, and offset), in face videos would greatly benefit for facial expression recognition systems. Previous works, considered combining, per AU, a discriminative frame-based Support Vector Machine (SVM) and a dynamic generative Hidden Markov Models (HMM), to detect the presence of the AU in question and its temporal segments in an input image sequence. The major drawback of HMMs, is that they do not model well time dependent dynamics as the ones of AUs, especially when dealing with spontaneous expressions. To alleviate this problem, in this paper, we exploit efficient duration modeling of the temporal behavior of AUs, and we propose hidden semi-Markov model (HSMM) and variable duration semi-Markov model (VDHMM) to recognize the dynamics of AU's. Such models allow the parameterization and inference of the AU's state duration distributions. Within our system, geometrical and appearance based measurements, as well as their first derivatives, modeling both the dynamics and the appearance of AUs, are applied to pair-wise SVM classifiers for a frame-based classification. The output of which are then fed as evidence to the HSMM or VDHMM for inferring AUs temporal phases. A thorough investigation into the aspect of duration modeling and its application to AU recognition through extensive comparison to state-of-art SVM-HMM approaches are presented. For comparison, an average recognition rate of 64.83 % and 64.66 % is achieved for the HSMM and VDHMM respectively. Our framework has several benefits: (1) it models the AU's temporal phases duration; (2) it does not require any assumption about the underlying structure of the AU events, and (3) compared to HMM, the proposed HSMM and VDHMM duration models reduce the duration error of the temporal phases of an AU, and they are especially better in recognizing the offset ending of an AU.

A survey of the dummy face and human face stimuli used in BCI paradigm.

It was proved that the human face stimulus were superior to the flash only stimulus in BCI system. However, human face stimulus may lead to copyright infringement problems and was hard to be edited according to the requirement of the BCI study. Recently, it was reported that facial expression changes could be done by changing a curve in a dummy face which could obtain good performance when it was applied to visual-based P300 BCI systems. In this paper, four different paradigms were presented, which were called dummy face pattern, human face pattern, inverted dummy face pattern and inverted human face pattern, to evaluate the performance of the dummy faces stimuli compared with the human faces stimuli. The key point that determined the value of dummy faces in BCI systems were whether dummy faces stimuli could obtain as good performance as human faces stimuli. Online and offline results of four different paradigms would have been obtained and comparatively analyzed. Online and offline results showed that there was no significant difference among dummy faces and human faces in ERPs, classification accuracy and information transfer rate when they were applied in BCI systems. Dummy faces stimuli could evoke large ERPs and obtain as high classification accuracy and information transfer rate as the human faces stimuli. Since dummy faces were easy to be edited and had no copyright infringement problems, it would be a good choice for optimizing the stimuli of BCI systems.

Hierarchical facial landmark localization via cascaded random binary patterns

The main challenge of facial landmark localization in real-world application is that the large changes of head pose and facial expressions cause substantial image appearance variations. To avoid high dimensional facial shape regression, we propose a hierarchical pose regression approach, estimating the head rotation, face components, and facial landmarks hierarchically. The regression process works in a unified cascaded fern framework with binary patterns. We present generalized gradient boosted ferns (GBFs) for the regression framework, which give better performance than ferns. The framework also achieves real time performance. We verify our method on the latest benchmark datasets and show that it achieves the state-of-the-art performance.

Moving portraits

We present an approach for generating face animations from large image collections of the same person. Such collections, which we call photobios, are remarkable in that they summarize a person's life in photos; the photos sample the appearance of a person over changes in age, pose, facial expression, hairstyle, and other variations. Yet, browsing and exploring photobios is infeasible due to their large volume. By optimizing the quantity and order in which photos are displayed and cross dissolving between them, we can render smooth transitions between face pose (e.g., from frowning to smiling), and create moving portraits from collections of still photos. Used in this context, the cross dissolve produces a very strong motion effect; a key contribution of the paper is to explain this effect and analyze its operating range. We demonstrate results on a variety of datasets including time-lapse photography, personal photo collections, and images of celebrities downloaded from the Internet. Our approach is completely automatic and has been widely deployed as the "Face Movies" feature in Google's Picasa.

S73: Visual mismatch negativity to changes in facial expressions in depressed and control participants

S73: Visual mismatch negativity to changes in facial expressions in depressed and control participants

Capitalizing on the success of romantic partners: A laboratory investigation on subjective, facial, and physiological emotional processing

Receiving a constructive, supportive response from romantic partners after sharing good news has been shown to magnify the positivity of events and predict healthy relationship outcomes. We conducted a laboratory social interaction to determine whether supportive responses to success led to changes in facial expressions, sympathetic arousal, and felt emotions. Our methodology allowed us to break down the sequence of capitalization support. In 69 romantic couples, we recorded emotional processing before, during, and after the task in both partners. Person A received performance feedback on a computer task and shared their success via text messages with Person B, who then reacted to this success. Supportive capitalization responses led to greater felt positive emotions and a trend for fewer negative emotions; effects were similar for givers and receivers of supportive responses. Facial expressions were also happier for people receiving supportive capitalization responses. Results suggest the importance of addressing the giving and receiving of capitalization support within the same social situation.

Pain control in horses: What do we really know?

Currently, approaches to pain control in horses are a mixture of art and science. Recognition of overt pain behaviours, such as rolling, kicking at the abdomen, flank watching, lameness or blepharospasm, may be obvious; subtle signs of pain can include changes in facial expression or head position, location in the stall and response to palpation or human interaction. Nonsteroidal anti-inflammatory drugs (i.e. phenylbutazone, flunixin meglumine and firocoxib), opioids (i.e. butorphanol, morphine and buprenorphine) and α2 -adrenergic agonists (i.e. xylazine, detomidine, romifidine and medetomidine) are the most commonly used therapeutic options. Multimodal therapy using constant-rate infusions of lidocaine, ketamine and/or butorphanol has gained popularity for severe pain in hospitalised cases. Drugs targeting neuropathic pain, such as gabapentin, are increasingly used for conditions such as laminitis. Optimal strategies for management of pain are based upon severity and chronicity, including special considerations for use of intra-articular or epidural delivery and therapy in foals. Strategies that aim to mitigate adverse effects associated with use of various analgesic agents are briefly discussed.

What can the Thatcher illusion tell us about face processing in the brain? Commentary on Psalta, Young, Thompson, and Andrews (2014).

Three decades ago Thompson (1980) discovered what is now a classic visual demonstration in psychology: that inverting the eyes and mouth of Margaret Thatcher's face passes largely unnoticed when the face is presented upside-down, even though the face appears grotesque in the upright orientation. Recently, Psalta et al. (2014) used fMRI to identify the neural basis of the Thatcher illusion and found that the face-selective superior temporal sulcus (fSTS), but not the fusiform face area (FFA) or the occipital face area (OFA), tracked the grotesque appearance of upright but not inverted Thatcherized faces. Referring to fSTS, the authors conclude: “Our results demonstrate clear evidence for orientation-dependent sensitivity to changes in facial expression in a key component of the neural network underlying face perception.” While we agree that fSTS is involved in processing face expression (Haxby and Gobbini, 2011), based on conceptual and statistical issues we argue that the conclusion of Psalta et al. (2014) is not supported by the data.

Detection of Blink and Facial Expression Changes using DCT Signs

The purpose of this study is to propose a method for detecting a blink and the facial expression changes from changes in DCT (Discrete Cosine Transform) signs and determining whether the subject is a real person or a photograph. Face detection was performed on two frames taken continuously with the camera, and DCT signs were used to determine whether or not changes in expression occurred in the detected facial images. First, we check whether there are any large changes such as changes in direction or tilting between the two frames of facial images. Next, we check for the presence of changes in expression using only the center portion of the facial image. If a change in expression occurs, the image taken with the camera is determined to be a real person. As a result, we were able to detect blinking or changes in expression from changes in DCT signs. We conclude that it is possible to determine whether a photographed subject is a photograph or a real person using the proposed method, and that this could be used to prevent impersonation in face detection system. The purpose of this study is to propose a method for detecting a blink and the facial expression changes from changes in DCT (Discrete Cosine Transform) signs and determining whether the subject is a real person or a photograph. Face detection was performed on two frames taken continuously with the camera, and DCT signs were used to determine whether or not changes in expression occurred in the detected facial images. First, we check whether there are any large changes such as changes in direction or tilting between the two frames of facial images. Next, we check for the presence of changes in expression using only the center portion of the facial image. If a change in expression occurs, the image taken with the camera is determined to be a real person. As a result, we were able to detect blinking or changes in expression from changes in DCT signs. We conclude that it is possible to determine whether a photographed subject is a photograph or a real person using the proposed method, and that this could be used to prevent impersonation in face detection system.The purpose of this study is to propose a method for detecting a blink and the facial expression changes from changes in DCT (Discrete Cosine Transform) signs and determining whether the subject is a real person or a photograph. Face detection was performed on two frames taken continuously with the camera, and DCT signs were used to determine whether or not changes in expression occurred in the detected facial images. First, we check whether there are any large changes such as changes in direction or tilting between the two frames of facial images. Next, we check for the presence of changes in expression using only the center portion of the facial image. If a change in expression occurs, the image taken with the camera is determined to be a real person. As a result, we were able to detect blinking or changes in expression from changes in DCT signs. We conclude that it is possible to determine whether a photographed subject is a photograph or a real person using the proposed method, and that this could be used to prevent impersonation in face detection system.

An optimized ERP brain–computer interface based on facial expression changes

Objective. Interferences from spatially adjacent non-target stimuli are known to evoke event-related potentials (ERPs) during non-target flashes and, therefore, lead to false positives. This phenomenon was commonly seen in visual attention-based brain–computer interfaces (BCIs) using conspicuous stimuli and is known to adversely affect the performance of BCI systems. Although users try to focus on the target stimulus, they cannot help but be affected by conspicuous changes of the stimuli (such as flashes or presenting images) which were adjacent to the target stimulus. Furthermore, subjects have reported that conspicuous stimuli made them tired and annoyed. In view of this, the aim of this study was to reduce adjacent interference, annoyance and fatigue using a new stimulus presentation pattern based upon facial expression changes. Our goal was not to design a new pattern which could evoke larger ERPs than the face pattern, but to design a new pattern which could reduce adjacent interference, annoyance and fatigue, and evoke ERPs as good as those observed during the face pattern. Approach. Positive facial expressions could be changed to negative facial expressions by minor changes to the original facial image. Although the changes are minor, the contrast is big enough to evoke strong ERPs. In this paper, a facial expression change pattern between positive and negative facial expressions was used to attempt to minimize interference effects. This was compared against two different conditions, a shuffled pattern containing the same shapes and colours as the facial expression change pattern, but without the semantic content associated with a change in expression, and a face versus no face pattern. Comparisons were made in terms of classification accuracy and information transfer rate as well as user supplied subjective measures. Main results. The results showed that interferences from adjacent stimuli, annoyance and the fatigue experienced by the subjects could be reduced significantly (p < 0.05) by using the facial expression change patterns in comparison with the face pattern. The offline results show that the classification accuracy of the facial expression change pattern was significantly better than that of the shuffled pattern (p < 0.05) and the face pattern (p < 0.05). Significance. The facial expression change pattern presented in this paper reduced interference from adjacent stimuli and decreased the fatigue and annoyance experienced by BCI users significantly (p < 0.05) compared to the face pattern.

Development of the Horse Grimace Scale (HGS) as a Pain Assessment Tool in Horses Undergoing Routine Castration

BackgroundThe assessment of pain is critical for the welfare of horses, in particular when pain is induced by common management procedures such as castration. Existing pain assessment methods have several limitations, which reduce the applicability in everyday life. Assessment of facial expression changes, as a novel means of pain scoring, may offer numerous advantages and overcome some of these limitations. The objective of this study was to develop and validate a standardised pain scale based on facial expressions in horses (Horse Grimace Scale [HGS]).Methodology/Principal FindingsForty stallions were assigned to one of two treatments and all animals underwent routine surgical castration under general anaesthesia. Group A (n = 19) received a single injection of Flunixin immediately before anaesthesia. Group B (n = 21) received Flunixin immediately before anaesthesia and then again, as an oral administration, six hours after the surgery. In addition, six horses were used as anaesthesia controls (C). These animals underwent non-invasive, indolent procedures, received the same treatment as group A, but did not undergo surgical procedures that could be accompanied with surgical pain. Changes in behaviour, composite pain scale (CPS) scores and horse grimace scale (HGS) scores were assessed before and 8-hours post-procedure. Only horses undergoing castration (Groups A and B) showed significantly greater HGS and CPS scores at 8-hours post compared to pre operatively. Further, maintenance behaviours such as explorative behaviour and alertness were also reduced. No difference was observed between the two analgesic treatment groups.ConclusionsThe Horse Grimace Scale potentially offers an effective and reliable method of assessing pain following routine castration in horses. However, auxiliary studies are required to evaluate different painful conditions and analgesic schedules.

Robust nose tip localization based on two-stage subclass discriminant analysis

Nose is one of the salient features in a human face, and its localization is important for face recognition, face pose recognition, 3D face reconstruction, etc. In this paper, a novel nose tip localization method is proposed, which is based on two-stage subclass discriminant analysis (SDA). At the first stage, some randomly selected image patches are used as negative samples for the training of SDA classifier, and nose is detected from the whole face image. The second stage refines nose tip position by using some nose context patches as negative samples for the training of SDA classifier. The proposed method detects nose from the whole face image and no a priori knowledge about the layout of face components is used. Experimental results on AR images show that the proposed method can achieve high nose tip localization rates, and is robust to changes of illumination and facial expression.

Accurate registration of cone-beam computed tomography scans to 3-dimensional facial photographs

Registering a 3-dimensional (3D) facial surface scan to a cone-beam computed tomography (CBCT) scan has various advantages. One major advantage is to compensate for the inaccuracy of the CBCT surface data. However, when registering CBCT and 3D facial scans, changes in facial expression, spatial soft-tissue changes, and differences in the patient's positioning can decrease the accuracy of the registration. In this study, we introduce a new 3D facial scanner that is combined with a CBCT apparatus. Our goal was to evaluate the registration accuracy of CBCT and 3D facial scans, which were taken with the shortest possible time between them. The experiment was performed with 4 subjects. Each patient was instructed to hold as still as possible while the CBCT scan was taken, followed immediately by the 3D facial surface scan. The images were automatically registered with software. The accuracy was measured by determining the degree of agreement between the soft-tissue surfaces of the CBCT and the 3D facial images. The average surface discrepancy between the CBCT facial surface and 3D facial surface was 0.60 mm (SD, 0.12 mm). Registration accuracy was also visually verified by toggling between the images of the CBCT and 3D facial surface scans while rotating the registered images. Registration of consecutively taken CBCT and 3D facial images resulted in reliable accuracy.

Dynamic stimuli demonstrate a categorical representation of facial expression in the amygdala

Face-selective regions in the amygdala and posterior superior temporal sulcus (pSTS) are strongly implicated in the processing of transient facial signals, such as expression. Here, we measured neural responses in participants while they viewed dynamic changes in facial expression. Our aim was to explore how facial expression is represented in different face-selective regions. Short movies were generated by morphing between faces posing a neutral expression and a prototypical expression of a basic emotion (either anger, disgust, fear, happiness or sadness). These dynamic stimuli were presented in block design in the following four stimulus conditions: (1) same-expression change, same-identity, (2) same-expression change, different-identity, (3) different-expression change, same-identity, and (4) different-expression change, different-identity. So, within a same-expression change condition the movies would show the same change in expression whereas in the different-expression change conditions each movie would have a different change in expression. Facial identity remained constant during each movie but in the different identity conditions the facial identity varied between each movie in a block. The amygdala, but not the posterior STS, demonstrated a greater response to blocks in which each movie morphed from neutral to a different emotion category compared to blocks in which each movie morphed to the same emotion category. Neural adaptation in the amygdala was not affected by changes in facial identity. These results are consistent with a role of the amygdala in category-based representation of facial expressions of emotion.

Gabor特徴を用いた顔画像からの微妙な表情変化の推定

Gabor特徴を用いた顔画像からの微妙な表情変化の推定

Dimensional information-theoretic measurement of facial emotion expressions in schizophrenia.

Altered facial expressions of emotions are characteristic impairments in schizophrenia. Ratings of affect have traditionally been limited to clinical rating scales and facial muscle movement analysis, which require extensive training and have limitations based on methodology and ecological validity. To improve reliable assessment of dynamic facial expression changes, we have developed automated measurements of facial emotion expressions based on information-theoretic measures of expressivity of ambiguity and distinctiveness of facial expressions. These measures were examined in matched groups of persons with schizophrenia (n = 28) and healthy controls (n = 26) who underwent video acquisition to assess expressivity of basic emotions (happiness, sadness, anger, fear, and disgust) in evoked conditions. Persons with schizophrenia scored higher on ambiguity, the measure of conditional entropy within the expression of a single emotion, and they scored lower on distinctiveness, the measure of mutual information across expressions of different emotions. The automated measures compared favorably with observer-based ratings. This method can be applied for delineating dynamic emotional expressivity in healthy and clinical populations.