The Profiling Potential of Computer Vision and the Challenge of Computational Empiricism

Computer vision and other biometrics data science applications have commenced a new project of profiling people. Rather than using 'transaction generated information', these systems measure the 'real world' and produce an assessment of the 'world state' - in this case an assessment of some individual trait. Instead of using proxies or scores to evaluate people, they increasingly deploy a logic of revealing the truth about reality and the people within it. While these profiling knowledge claims are sometimes tentative, they increasingly suggest that only through computation can these excesses of reality be captured and understood. This article explores the bases of those claims in the systems of measurement, representation, and classification deployed in computer vision. It asks if there is something new in this type of knowledge claim, sketches an account of a new form of computational empiricism being operationalised, and questions what kind of human subject is being constructed by these technological systems and practices. Finally, the article explores legal mechanisms for contesting the emergence of computational empiricism as the dominant knowledge platform for understanding the world and the people within it

Analysis of Facial Expressions with Respect to Navarasas in Bharathanatym Styles Using Image Processing

Facial expression analysis with respect to Bharathanatyam a classical dance style of south India is studied in this paper by using image processing techniques and several properties associated with the face are taken into consideration. The emotional changes result in the changes in the facial expression. Accordingly the curvatures developed on the face and the dimensions of the objects on the face such as eyebrows, lips and the area of the mouth also change. Naturally there exist changes in the intensity of the pixels corresponding to these objects. The natural eyes can distinguish these sharp changes in both the cases and understand the facial expressions. The experimental results predicted a definite change in every trail. These results can also be used as a tool to design intelligent system which recognizes different emotions of people in different environment. The results are found to be of immense scientific and psychological interest

Implicit And Explicit Racial Attitudes: Moderation Of Racial Typicality Evaluations

Previous research has shown that racial images representing more typical Afrocentric phenotypic characteristics result in more negative evaluations, whether assessed by explicit or implicit attitudes measures. However, the factors that define and moderate the perception of racial typicality have not been sufficiently explored. The current research investigated additive and interactive influences of skin tone and facial physiognomy on racial typicality evaluations, as well as the degree to which those effects were moderated by explicit and implicit racial attitudes, ethnicity of participants, and availability of cognitive resources. Using a 6-point scale ranging from very African American to very Caucasian, participants: N = 250) judged faces varying on 10 levels of facial physiognomy: from very Afrocentric to very Eurocentric) and 10 levels of skin color: from very dark to very light). Additionally, time constraints were manipulated by having participants complete the racial typicality judgments three times without a response deadline, with a deadline equal to their median response during the no-deadline condition, and with a deadline equal to their 25th percentile response during the no-deadline condition. Skin color and facial physiognomy interacted to influence racial typicality ratings, and this interaction was further qualified by the time constraint manipulation. Under time constraints, participants primarily relied on skin color when rating faces of extreme levels of facial physiognomy, whereas they relied on both skin color and facial physiognomy when rating faces of intermediate levels of facial physiognomy. Other results indicated that the relationship between skin color and participants\u27 ratings of racial typicality was stronger for those with higher implicit racial attitudes. European American and Asian American participants relied upon skin color more than African American participants, and African American participants relied upon facial physiognomy more than European American and Asian American participants. Conceptual, methodological and practical implications for race-relevant decisions are discussed

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

© 2015 The Author(s) 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

Notes on the semiotics of face recognition

Perceiving and recognizing others via their faces is of pivotal importance. The ability to perceive others in the environment – to discern between friends and foes, selves and others – as well as to detect and seek to predict their possible moves, plans, and intentions, is a set of skills that has proved to be essential in the evolutionary history of humankind. The aim of this study is to explore the subject of face recognition as a semiotic phenomenon. The scope of this inquiry is limited to face perception by the human species. The human face is analysed on the threshold between biological processes and cultural processes. We argue that the recognition of likenesses has a socio-cultural dimension that should not be overlooked. By drawing on Georg Lichtenberg’s remarks on physiognomy, we discuss the critique of the semiotic bias, the association of ideas, and the mechanism of typification involved in face recognition. Face typification is discussed against the background of face recognition and face identification. We take them as three gradients of meaning that map out a network of relationships concerning different cognitive operations that are at stake when dealing with the recognition of faces.    &nbsp

Feelings on Faces. From Physiognomics to Neuroscience

Of all the ways in which the outward signs of the body express inner feeling, physiognomy and gesture have been the most studied. In this essay, I will deal with physiognomy and its related form, pathognomy. Gesture must wait for another occasion. Both physiognomy and the study of gesture, at least in their traditional and historical forms, have generally been taken as the very type of disciplines that have ignored the pressures of culture and difference, failing to take into account the social construction both of interiority and of its outward manifestations. It is true that physiognomy and pathognomy, like the study of gesture, sought to establish fixed correlations between expression and emotion, when in fact the relationship between particular expressions and specific emotions are very oft en the product of cultural and contextual constraints, pressures, and circumstance. Or so the usual insistence runs. Hence, for example, the continuing high scepticism about projects like Charles Le Brun's and the complete disdain of the physiognomic projects of Lavater. Even Darwin's great work on the subject has only recently begun to return to favor (though only hesitantly amongst academic humanists), despite its clear articulation of the role of cultural constraints on emotional expression) In what follows, I will set out how, contrary to conventional views of the neurosciences as reductionist, the neuroscience of facial expression and its emotional recognition does not in fact impugn this role, but substantially enhances it. My aim is to suggest that the role of culture in the construction of both feeling and expression is considerably more complex than current views of cultural determinism seem to allow

LIKE FATHER, LIKE SON: STEREOTYPICAL BLACK FACIAL FEATURES IN CHILDREN CAUSING TROUBLE

This present study investigated whether face-type (stereotypical or nonstereotypical) facilitates stereotype-consistent categorization and decision-making. Previous literature regarding adults has suggested an associative link between stereotypically Black facial features and assumed criminality. This study seeks to extend these findings by investigating whether the same heuristic processes that underpin biased decisions regarding adult phenotypic racially stereotypical features (e.g., broad nose, full lips) extend to children’s faces. That is, do the negative stereotypes (i.e., criminal Black male) that influence face-type judgments in adults extend to child face-type judgements as well. In two studies testing face-type categorization and disciplinary judgments, people were more likely to miscategorize children with stereotypical faces into negative roles more than positive roles. People were also more likely to increase their disciplinary judgments from one infraction to another for children with stererotypical faces compared to atypical faces. Results suggest that face-type cues do extend to children and also engender negative associations

Physiognomic Artificial Intelligence

The reanimation of the pseudosciences of physiognomy and phrenology at scale through computer vision and machine learning is a matter of urgent concern. This Article—which contributes to critical data studies, consumer protection law, biometric privacy law, and antidiscrimination law—endeavors to conceptualize and problematize physiognomic artificial intelligence (“AI”) and offer policy recommendations for state and federal lawmakers to forestall its proliferation. Physiognomic AI, as this Article contends, is the practice of using computer software and related systems to infer or create hierarchies of an individual’s body composition, protected class status, perceived character, capabilities, and future social outcomes based on their physical or behavioral characteristics. Physiognomic and phrenological logics are intrinsic to the technical mechanism of computer vision applied to humans. This Article observes how computer vision is a central vector for physiognomic AI technologies and unpacks how computer vision reanimates physiognomy in conception, form, and practice and the dangers this trend presents for civil liberties. This Article thus argues for legislative action to forestall and roll back the proliferation of physiognomic AI. To that end, it considers a potential menu of safeguards and limitations to significantly limit the deployment of physiognomic AI systems, which hopefully can be used to strengthen local, state, and federal legislation. This Article foregrounds its policy discussion by proposing the abolition of physiognomic AI. From there, it posits regimes of U.S. consumer protection law, biometric privacy law, and civil rights law as vehicles for rejecting physiognomy’s digital renaissance in AI. Specifically, it contends that physiognomic AI should be categorically rejected as oppressive and unjust. Second, it argues that lawmakers should declare physiognomic AI unfair and deceptive per se. Third, it proposes that lawmakers should enact or expand biometric privacy laws to prohibit physiognomic AI. Fourth, it recommends that lawmakers should prohibit physiognomic AI in places of public accommodation. It also observes the paucity of procedural and managerial regimes of fairness, accountability, and transparency in ad- dressing physiognomic AI and attend to potential counterarguments in support of physiognomic AI