Color Face Research Articles

Accelerating Racial Activism in STEM Higher Education by Institutionalizing Equity Ethics

Background/Context: The United States invests in STEM education, but this investment is racialized and political. The country wants to maintain global economic domination, but there are also calls to diversify the STEM workforce (Baber, 2015; Basile & Lopez, 2015; Vakil & Ayers, 2019). This context leaves Black and Brown people to navigate racially hostile, toxic, and oppressive STEM learning and working environments (Bullock, 2017; Erete et al., 2020; Wright & Riley, 2021). Purpose/Objective/Research Question/Focus of Study: This conceptual paper offers strategies for institutionalizing equity ethics in STEM higher education. The paper attends to the core components of equity ethics and its possibilities while identifying structural constraints. Equity ethics is an equity-minded perspective that focuses on leveraging the multiple forms of knowledge associated with understanding and engaging the natural world to foster an oppression-free society that specifically enhances the lives of Black and Brown people. We also examine specific cases of STEM education and research scholars and practitioners who are committed to engaging and uplifting racially minoritized communities through the intersection of STEM and justice. Research Design: This conceptual paper takes a qualitative approach. It uses the existing literature to review the current state of diversity in STEM, the major components of an equity ethic, the structural and institutional barriers people of color face in STEM higher education, and how equity ethics may be institutionalized. In particular, we highlight examples of equity ethics in action to provide models for action and policy change. Conclusions/Recommendations: Institutionalized equity ethics at the mid-institutional level (e.g., departments and units) would require all faculty to mentor Black and Brown STEM students through critical transitions. We also recommend revising department- and unit-level policies and practices around access to resources that are critical for STEM achievement and knowledge production. Although expanding and sustaining financial investments in equity-focused endeavors is required, these investments must also come with the power and agency to transform institutional structures around STEM access, learning, and innovation. Transformation of top-level policies and practices could include changes to institutional admissions processes and ensuring that racist gatekeeping mechanisms are removed, while also requiring senior-level administrators to have training in racial justice ideologies and praxes. Building equity ethics into STEM higher education is essential to creating a more just and equitable STEM ecosystem.

Effectiveness Of The Omni Rate Of Perceived Exertion Color Face Scale At Self-regulating Exercise Intensity

Effectiveness Of The Omni Rate Of Perceived Exertion Color Face Scale At Self-regulating Exercise Intensity

Intensive Naming: Concerted Cultivation and Flexible Ethnicity among U.S. Middle-Class Mexican-Origin Parents

AbstractSelecting a name for a child represents an important symbolic and cultural decision. As social labels, names serve as identity markers that influence how their bearers are perceived and treated. Sociologists are increasingly taking advantage of the study of names, with most adopting a quantitative approach and analyzing names as outcomes. Less is known about the social meanings surrounding names and motivations behind naming decisions, the examination of which can provide insight into parental aspirations, the reproduction of class, and strategies for ethnoracial integration. Drawing on 72 in-depth interviews with Mexican-origin respondents, I show how middle-class parents leverage first names to meet their goals of creating middle-class, multicultural children. I find respondents practice intensive naming, a strategic pre-birth form of parenting, where parents carefully assess naming options with the goal of maximizing their children’s opportunities vis-à-vis ethnoracial integration and class distinction. Specifically, I show how parents chose names that are ethnically flexible and signal middle-class status to facilitate their successful integration into various ethnoracial contexts. These findings illustrate the unique challenges parents of color face in their intensive parenting efforts and how names are used as cultural tools to position the next generation in desirable class and ethnoracial terms.

Assessing color cues of development, breeding status and reproductive condition in captive golden lion tamarins (Leontopithecus rosalia).

Color signals play an important role in intraspecific communication and are well studied in catarrhine primates, which exhibit uniform trichromatic vision that is well suited to detecting such signals. Platyrrhine primates exhibit polymorphic color vision with different individuals possessing different color vision types in most species. Intriguingly, some platyrrhine species exhibit bare faces, which are convergent with those of catarrhines. However, putative functions of bare-faced color signals in platyrrhines remain largely unexplored. We measured facial skin color of five captive golden lion tamarins (Leontopithecus rosalia) using color-calibrated digital photography and modeled these colors to the visual systems of the species. Our results show that facial coloration is different between infant and older adults and varies across reproductive condition, but not between breeding and nonbreeding adults. While preliminary, our study suggests that facial coloration may be involved in sociosexual signaling in golden lion tamarins, and provides intriguing evidence that we hope might stimulate more studies of bare-faced signaling in platyrrhines.

Comparison of regression techniques to predict attractiveness from facial colour cues

Comparison of regression techniques to predict attractiveness from facial colour cues

What Is Written on a Dog's Face? Evaluating the Impact of Facial Phenotypes on Communication between Humans and Canines.

Facial phenotypes are significant in communication with conspecifics among social primates. Less is understood about the impact of such markers in heterospecific encounters. Through behavioral and physical phenotype analyses of domesticated dogs living in human households, this study aims to evaluate the potential impact of superficial facial markings on dogs' production of human-directed facial expressions. That is, this study explores how facial markings, such as eyebrows, patches, and widow's peaks, are related to expressivity toward humans. We used the Dog Facial Action Coding System (DogFACS) as an objective measure of expressivity, and we developed an original schematic for a standardized coding of facial patterns and coloration on a sample of more than 100 male and female dogs (N = 103), aged from 6 months to 12 years, representing eight breed groups. The present study found a statistically significant, though weak, correlation between expression rate and facial complexity, with dogs with plainer faces tending to be more expressive (r = -0.326, p ≤ 0.001). Interestingly, for adult dogs, human companions characterized dogs' rates of facial expressivity with more accuracy for dogs with plainer faces. Especially relevant to interspecies communication and cooperation, within-subject analyses revealed that dogs' muscle movements were distributed more evenly across their facial regions in a highly social test condition compared to conditions in which they received ambiguous cues from their owners. On the whole, this study provides an original evaluation of how facial features may impact communication in human-dog interactions.

Black Lives Still Matter: Freedom Schools as an Embodiment of Critical Literacy Through Reflection and Action

The continuation of racial inequities in the United States has ignited the recent Black Lives Matter Movement, a protest of police brutality and gun violence. Black lives matter in public school classrooms, too—where students of color face barriers to equitable educational experiences. The Children's Defense Fund Freedom School program is a major component in developing critical literacy skills through critique, inquiry, and transformation through social justice and action. Critical literacy is enacted through identity—mainly as difference, self, consciousness, narrative, and positionality. Historical and contemporary relevance of Freedom Schools connects to the urgency of the Black Lives Matter Movement.

A Study on the Changing of Biophysical Properties of the Facial Skin according to Aging

Purpose: This study aimed to analyze the differences in skin characteristics such as crow’s feet, visible and invisible spots, pores in the left and right cheek areas of the face, porphyrins, brown spots, and skin color and texture with increasing age.Methods: This study utilized Visia-CR software Mirror® to capture images of the entire face of 457 individuals aged 30–60 years. Facial skin characteristics were analyzed using image analysis software, VAESTRO, and a toolkit. The analysis of facial skin characteristics according to age was performed using one-way analysis of variance to test for significance, followed by Scheffe’s post-hoc test.Results: Significant differences in age-related crow’s feet, visible and invisible spots, brown spots on the left and right cheeks, and skin texture were observed in all age groups, except for groups in their 50s and 60s. Porphyrins, depending on age, showed significant differences between the mean values of the 30s and all other age groups and those of the 40s and 60s. Significant differences in L* and a* according to age were observed between the mean values of the 30s and 50s–60s and those of the 40s and 60s. Significant differences in age-dependent b* were observed between the mean values of the 30s and all other age groups.Conclusion: This study found significant differences in wrinkles, spots, brown spots, and skin color (L*, a*, and b*) with age. However, there were no significant difference in the pores of the facial skin and b* with increasing age. Based on this result, L* and a* are likely to require further research for the age groups in the 30s and 40s, 40s and 50s, and 50s and 60s. In addition, pores and b* require follow-up studies on morphological changes of the facial skin regardless of aging.

Barriers and Facilitators to the Online Delivery of a School-Based Intervention to Reduce Racial Trauma.

Students of color face disproportionate rates of adverse childhood experiences, including racial discrimination in school settings. Effective interventions strategies are needed to address school-based racial trauma. Link for Equity was designed to be a culturally-responsive trauma-informed intervention that includes universal cultural humility training for teachers. As a result of the COVID-19 pandemic, the in-person trauma-informed cultural humility training was adapted for online delivery. The purpose of this study was to assess barriers and facilitators that impacted online delivery of the training. We conducted semi-structured interviews with 25 high school teachers from three public school districts in the Midwestern United States who participated in the online training. Interview transcripts were coded by two team members, and thematic analysis was utilized. Barriers and facilitators to online delivery were identified across five domains: receptivity, logistics, engagement, comfort, and application. The implications of these barriers and facilitators are discussed and tailored recommendations for the virtual delivery of culturally-responsive trauma-informed interventions to reduce racial discrimination in schools are provided.

Face recognition based on machine learning

Due to its widespread use, face recognition has emerged in the past 20 years as one of the most pervasive biometric identification technology disciplines. This paper briefly summarizes the history of face recognitions development, identifies the technologys present use cases, introduces the main methods of face recognition in detail from the perspective of machine learning and prospects for the future development of this technology. The result shows that this technology still faces many challenges, such as the problem of recognizing different expressions on the same face, the problem of recognizing twins and similar faces, the problem of using the color information of color face images efficiently and so on.

Scholars from Underrepresented Groups in Engineering and the Social Sciences (SURGE) Capacity in Disasters: The Benefits and Challenges of Mentoring for Racial and Ethnic Minority Graduate Students

Objective: The purpose of this study was to evaluate the mentoring program of the Minority Scholars from Under-Represented Groups in Engineering and the Social Sciences (SURGE) Capacity in Disasters initiative, a pilot program that aimed to address the challenges that graduate students of color face in academic programs. SURGE promotes mentoring and professional development through its mentoring program for Science, Technology, Engineering, and Mathematics (STEM) students. Methods: Data collection involved distributing online surveys designed in Qualtrics to mentors and mentees five months after the SURGE program’s initiation. Separate surveys were created for student mentees and faculty mentors in order to collect feedback about the mentoring program. Mentees and mentors were also asked to rate their satisfaction with the specific individuals in their mentoring network so that the evaluation team could identify issues that arose across participants. Results: We found that students had several motivations for and expectations from SURGE. A majority of the students found the SURGE mentoring program to have been at least somewhat valuable in helping them achieve these expectations. Nonetheless, students did identify a few challenges, namely lack of swift responsiveness from some mentors, not enough guidance on navigating the mentor-mentee relationship, and little to no in-person interaction. While half of the students mentioned that some individuals within their mentoring team were hard to reach, a majority remained satisfied with the overall responsiveness of their mentors. This suggests that the many-to-many mentoring model helped to ensure none were entirely dissatisfied on this measure. Conclusions: These findings support previous research and show promise for mentoring as an effective intervention to the challenges that underrepresented students face in their academic programs and for their retention and representation, particularly in hazards and disaster-related fields. Implications: Overall, given the unique barriers and challenges to retention for minority students in graduate programs, it is important to understand the mentoring needs of underrepresented students in order to provide the best possible help to them during what can be an extraordinarily difficult transition into academia. It is especially crucial to do this for underrepresented students in the fields of hazards and disaster research and practice, as their contributions and perspectives are needed to address social disparities and inequities.

Awakening: Losing then finding myself in STEMM

For over 25 years, Dr. Elsie Calderón-Spencer has witnessed the effects of DEI initiatives in STEMM. She shares her story, centered on her experiences as an Afro-Latina woman navigating STEMM higher education and how they reflect the challenges Black and Indigenous people of color face.

Gesture Recognition based Virtual Mouse and Keyboard

Abstract: The field of computer vision has advanced significantly, enabling computers to identify their users using simple programs based on image processing. This technology has been widely used in various day-to-day applications, such as face recognition, color detection, and autonomous driving. This research project aims to use computer vision to develop an optical mouse and keyboard that can be operated through hand movements. The computer camera will capture images of different hand gestures made by the user, and the mouse pointer or cursor on the computer screen will move accordingly. Different hand gestures can be used to execute right and left-clicks. Similarly, the keyboard functions can be performed using different hand actions, such as using a finger to select an alphabet and a four-digit swipe left or right. The virtual mouse and keyboard can be used wirelessly or externally, and the only hardware required for the project is a webcam.

Probabilistic quaternion collaborative representation and its application to robust color face identification

Quaternion representation (QR) has been shown to be an effective tool for image processing by modelling color images as quaternion matrices. However, previous QR based classification (QRC) methods overlook the labels of training data and may lead to sub-optimal results. In this article, we propose a Probabilistic Quaternion Collaborative Representation (ProQCR) method based on maximum likelihood estimation with application to color face identification. The proposed ProQCR method has the following merits: (1) Full supervision: In the representation and classification processes, the ProQCR method exploits the label information of training data, in contrast to prior methods using such supervision information only in the classification step. (2) Multi-channel integrality: ProQCR represents multiple color channels of each test color image as a quaternion linear combination of training data in a holistic manner. (3) Robustness: Equipped with the quaternion Huber loss function, ProQCR is robust against gross corruption in the test data. Experiments on benchmark databases demonstrate the effectiveness and robustness of ProQCR for color face identification.

Method and analysis of color changes of facial skin after applying skin makeup

This study investigated facial skin color differences before and after makeup. Toward this goal, a photo gauge, devised with a pair of color checkers as a reference, collected face images. In addition, color calibration and a deep-learning method extracted the color values of representative areas of facial skin. The photo gauge photographed 516 Chinese females before and after applying makeup. Then, the collected images were calibrated by referencing skin color patches, and the lower cheek regions’ pixel colors were extracted using open-source computer vision libraries. Following the visible color spectrum of humans, the color values were computed in L*, a*, and b* of CIE1976L*a*b*. The results showed that the facial colors of the Chinese females changed to become brighter, less reddish, and less yellowish after applying the makeup, resulting in a paler skin tone. During the experiment, subjects were given five varieties of liquid foundation to choose one sample that best fits their skin. However, we failed to find any noticeable relationship between the individual’s facial skin color characteristics and the liquid foundation selected. In addition, 55 subjects were identified according to their makeup use frequency and skill, but their color changes did not differ from the other subjects. This study provided quantitative evidence of makeup trends in the Shanghai region in China, and the method proposes a novel approach toward remote skin color research.

Modal Regression-Based Graph Representation for Noise Robust Face Hallucination.

Manifold learning-based face hallucination technologies have been widely developed during the past decades. However, the conventional learning methods always become ineffective in noise environment due to the least-square regression, which usually generates distorted representations for noisy inputs they employed for error modeling. To solve this problem, in this article, we propose a modal regression-based graph representation (MRGR) model for noisy face hallucination. In MRGR, the modal regression-based function is incorporated into graph learning framework to improve the resolution of noisy face images. Specifically, the modal regression-induced metric is used instead of the least-square metric to regularize the encoding errors, which admits the MRGR to robust against noise with uncertain distribution. Moreover, a graph representation is learned from feature space to exploit the inherent typological structure of patch manifold for data representation, resulting in more accurate reconstruction coefficients. Besides, for noisy color face hallucination, the MRGR is extended into quaternion (MRGR-Q) space, where the abundant correlations among different color channels can be well preserved. Experimental results on both the grayscale and color face images demonstrate the superiority of MRGR and MRGR-Q compared with several state-of-the-art methods.

Through a New Lens: Skin-Grafted Free Flaps and Objective Facial Skin Color Matching.

Background: Head and neck ablative surgery can impose aesthetic disfigurement, particularly when severe color mismatch exists between native and reconstructed facial skin. To date, the accuracy, objectivity, and modifiability of facial skin color matching remains poorly understood. Objective: To measure skin color match outcomes after head and neck reconstruction using handheld colorimetry. Methods: Patients undergoing complex head and neck reconstruction involving facial skin were included. A variety of skin paddle donor sites were studied, including split-thickness skin graft (STSG) placement over myocutaneous or adipofasciocutaneous free flaps after de-epithelization. Skin color match (deltaE) was measured during follow-up using a handheld colorimeter. Results: Forty-seven patients were included, with median age 69. The most common flap type was the anterolateral thigh (n = 31, 66%). Twenty patients underwent STSG to the skin paddle. DeltaE measurements among the patients with STSGs demonstrated better color match (lowest deltaE), compared with patients with unaltered skin paddles (3.4 ± 1.0 vs. 6.5 ± 2.5, p < 0.0001). Conclusion: We found the use of STSGs over de-epithelialized myogenous or adipofasciocutaneous flaps improves color match, as measured by handheld colorimetry.

Shades of Feeling: How Facial Color Variations Influence Emotional and Health Perception

Shades of Feeling: How Facial Color Variations Influence Emotional and Health Perception

Male Guppies Recognize Familiar Conspecific Males by Their Face

Individual recognition is a necessary cognitive ability for the maintenance of stable social relationships. Recent studies have shown that like primates, some fish species can distinguish familiar fish from unfamiliar strangers via face-recognition. However, the taxa of the studied fish species are restricted (within Perciformes) and the visual signal used for the recognition of fish remains unclear. Here, we investigated the visual signal for individual-recognition in males of a sexually dichromatic guppy (Poecilia reticulata, Cyprinodontiformes). Using guppy males, we examined the hypothesis that fish distinguish between familiar individuals and unknown strangers by their faces rather than by body coloration. We randomly presented focal fish with four types of composite photo-models: familiar (familiar-face and familiar-body = F/F), stranger (stranger-face and stranger-body = S/S), familiar face combined with stranger body (F/S) and stranger face combined with familiar body (S/F). Focal males infrequently attacked familiar-face models but frequently attacked stranger-face models, regardless of body types. These behavioral reactions indicate that guppy males discriminate between familiar and stranger males by their face, not body coloration with wide variation. Importantly, male faces contain clear individual-variation in white/metallic colored patches on the operculum visible for humans. Considering the photo-model, our results suggest that these patches might be an important visual stimulus for face-recognition in guppy males, like some cichlids. Comparative examination among males of different guppy variants, including wild type phenotype, suggests that the face color-patch is stable regardless of variation in body color, with a different genetic mechanism potentially underlying face and body colors.

Online New Media Oriented Privacy Data Recognition Mechanism Based on Deep Learning

Although the current face de-recognition algorithm can effectively protect the user’s identity, it will change the original attributes of the image, destroy the visual effect, or change the characteristics of the image to varying degrees. Traditional methods such as pixelation and occlusion can effectively realize face de-recognition, but the processed image cannot be used for basic processing such as face statistics and expression recognition, which greatly destroys the usability of the image in the field of online new media. In order to preserve more attributes of the original image and reduce the changes of facial skin color and texture features caused by the above de-recognition algorithm’s operation on the whole facial area, this paper proposes a privacy protection model of face image based on generative adversarial network and facial feature analysis. Our model realizes face recognition based on changing the original image as little as possible. Specifically, we identify and extract features from fixed parts in face images, including eyes, nose, mouth, eyebrows, and cheeks. Then, we designed a face privacy recognition and protection model based on conditional generative adversarial networks. We verify our proposed method on two most commonly used face datasets in face research, namely CelebFaces Attributes and Labeled Faces in the Wild, and the results show that our proposed method achieve better performance compared with other face privacy protection methods.