Changes In Facial Expression Research Articles

A Survey of Feature Base Methods for Human Face Detection

The human face is among the most significant objects in an image or video, it contains many important information and specifications, also is required to be the cause of almost all achievable look variants caused by changes in scale, location, orientation, pose, facial expression, lighting conditions and partial occlusions. It plays a key role in face recognition systems and many other face analysis applications. We focus on the feature based approach because it gave great results on detect the human face. Face feature detection techniques can be mainly divided into two kinds of approaches are Feature base and image base approach. Feature base approach tries to extract features and match it against the knowledge of the facial features. This paper gives the idea about challenging problems in the field of human face analysis and as such, as it has achieved a great attention over the last few years because of its many applications in various domains. Furthermore, several existing face detection approaches are analyzed and discussed and attempt to give the issues regarding key technologies of feature base methods, we had gone direct comparisons of the method's performance are made where possible and the advantages/ disadvantages of different approaches are discussed.

Cultural-based visual expression: emotional analysis of human face via Peking Opera Painted Faces (POPF)

Peking Opera as a branch of Chinese traditional cultures and arts has a very distinct colourful facial make-up for all actors in the stage performance. Such make-up is stylised in nonverbal symbolic semantics which all combined together to form the painted faces to describe and symbolise the background, the characteristic and the emotional status of specific roles. A study of Peking Opera Painted Faces (POPF) was taken as an example to see how information and meanings can be effectively expressed through the change of facial expressions based on the facial motion within natural and emotional aspects. The study found that POPF provides exaggerated features of facial motion through images, and the symbolic semantics of POPF provides a high-level expression of human facial information. The study has presented and proved a creative structure of information analysis and expression based on POPF to improve the understanding of human facial motion and emotion.

1-A-D-17. The influence of spatial frequency and autistic traits on the perception of change in facial expression: An event-related potential study

We studied visual information process of dynamic facial expressions in autism spectrum condition. Our aim was to investigate how P1 and N170 ERP components are affected by an interaction with the spatial frequencies and autistic traits. We filtered low spatial frequency information or high spatial frequency information from grayscale face pictures. These face stimuli consisted of neutral, happy and angry expressions. Sixteen healthy participants observed the change in facial expression (Miyoshi et al., 2004). They were assessed autistic traits by Autism-Spectrum Quotient Japanese version (AQ, Baron-Cohen et al., 2001; Wakabayashi et al., 2004). When participants viewed the change in low spatial frequency facial expression, P1 amplitude from parieto-occipital electrode was attenuated in participants with high AQ group. In the high spatial frequency condition, participants with greater autistic trait showed more smaller N170 amplitude to the change in facial expression at the posterior temporal site. Our findings suggest that individuals with high autistic traits may have aberrant visual processing of spatial frequency information.

Context-Sensitive Dynamic Ordinal Regression for Intensity Estimation of Facial Action Units

Modeling intensity of facial action units from spontaneously displayed facial expressions is challenging mainly because of high variability in subject-specific facial expressiveness, head-movements, illumination changes, etc. These factors make the target problem highly context-sensitive. However, existing methods usually ignore this context-sensitivity of the target problem. We propose a novel Conditional Ordinal Random Field (CORF) model for context-sensitive modeling of the facial action unit intensity, where the W5+ (who, when, what, where, why and how) definition of the context is used. While the proposed model is general enough to handle all six context questions, in this paper we focus on the context questions: who (the observed subject), how (the changes in facial expressions), and when (the timing of facial expressions and their intensity). The context questions who and howare modeled by means of the newly introduced context-dependent covariate effects, and the context question when is modeled in terms of temporal correlation between the ordinal outputs, i.e., intensity levels of action units. We also introduce a weighted softmax-margin learning of CRFs from data with skewed distribution of the intensity levels, which is commonly encountered in spontaneous facial data. The proposed model is evaluated on intensity estimation of pain and facial action units using two recently published datasets (UNBC Shoulder Pain and DISFA) of spontaneously displayed facial expressions. Our experiments show that the proposed model performs significantly better on the target tasks compared to the state-of-the-art approaches. Furthermore, compared to traditional learning of CRFs, we show that the proposed weighted learning results in more robust parameter estimation from the imbalanced intensity data.

Positioning corners of human mouth based on local gradient operator

Face recognition has widespread applications in monitoring system, public security and home entertainment etc.. However, in practical application, there are many problems needed to be solved in face recognition technology. This paper presents a method to detect and locate accurately facial feature points based on local gradient operator. With Adaboost algorithm, we first detect roughly the mouth area in the face image, and then extract contours of mouth using local gradient operator. Finally, we use Ostu threshold to extract the binary contour around mouth corners according to the precise location of chain code tracing. Experimental results show that local gradient operator can detect and locate rapidly and accurately human mouth, and it is relatively robust against change of facial expressions as well as noise, which helps to improve face recognition rate.

Quantitative anatomical analysis of facial expression using a 3D motion capture system: Application to cosmetic surgery and facial recognition technology.

The topography of the facial muscles differs between males and females and among individuals of the same gender. To explain the unique expressions that people can make, it is important to define the shapes of the muscle, their associations with the skin, and their relative functions. Three-dimensional (3D) motion-capture analysis, often used to study facial expression, was used in this study to identify characteristic skin movements in males and females when they made six representative basic expressions. The movements of 44 reflective markers (RMs) positioned on anatomical landmarks were measured. Their mean displacement was large in males [ranging from 14.31 mm (fear) to 41.15 mm (anger)], and 3.35-4.76 mm smaller in females [ranging from 9.55 mm (fear) to 37.80 mm (anger)]. The percentages of RMs involved in the ten highest mean maximum displacement values in making at least one expression were 47.6% in males and 61.9% in females. The movements of the RMs were larger in males than females but were more limited. Expanding our understanding of facial expression requires morphological studies of facial muscles and studies of related complex functionality. Conducting these together with quantitative analyses, as in the present study, will yield data valuable for medicine, dentistry, and engineering, for example, for surgical operations on facial regions, software for predicting changes in facial features and expressions after corrective surgery, and the development of face-mimicking robots.

The implicit need for power predicts recognition speed for dynamic changes in facial expressions of emotion

Facial expressions of emotion (FEEs) have been portrayed as potent (dis-) incentives for power-motivated perceivers, because they signal the strength of a sender’s dominance (Stanton et al. in Implicit motives. Oxford University Press, New York, pp 245–278, 2010). Here, we tested the hypothesis that individuals with a high implicit power motive (nPower), who have a disposition to seek (emotional) impact on others, would be faster at recognizing FEEs than individuals low in nPower. In a task employing videos of morphed FEEs, which are gradually changing from neutral to either anger, joy or surprise, higher nPower predicted faster recognition of the displayed emotion as well as a tendency to misidentify joy as anger. Our findings suggest that one way through which people high in nPower are socially influential is their enhanced sensitivity to emotional signals in their social environment.

Fabrication of graphene/free-standing nanofibrillar PEDOT/P(VDF-HFP) hybrid device for wearable and sensitive electronic skin application

In this work, we describe a simple method for the fabrication of a new class of graphene/free-standing nanofibrillar PEDOT/P(VDF-HFP) nanohybrid E-skin device. This E-skin exhibits enhanced contact surface area and piezo-resistivity with an extremely high gauge factor (320) under tensile strain, which combine to yield very high sensitivity to pressure (limit of detection=0.5Pa). Signals from even very weak motion, such as changes in facial expression and the pulse in the wrist, can be detected. Furthermore, this E-skin is sufficiently durable and reproducible. The E-skin device does not exhibit measurable changes in performance or observable signs of physical deterioration, even after over 1000 strain cycles, and is wearable and sufficiently biocompatible to be placed inside clothing or against human skin without causing irritation.

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.