Research on video-based face recognition has started getting increased attention in the past few years. Algorithms developed for video have an advantage from the availability of plentitude of frames in videos to extract information from. Despite this fact, most research in this direction has limited the scope of the problem to the application of still image-based approaches to some selected frames on which 2D algorithms are expected to perform well. It can be realized that such an approach only uses the spatial information contained in video and does not incorporate the temporal structure.Only recently has the intelligence community begun to approach the problem in this direction. Video-based face recognition algorithms in the last couple of years attempt to simultaneously use the spatial and temporal information for the recognition of moving faces. A new face recognition method that falls into the category of algorithms that adopt spatio-temporal representation and utilizes dynamic information extracted from video is presented. The method was designed based on the hypothesis that the strain pattern exhibited during facial expression provides a unique "fingerprint" for recognition. First, a dense motion field is obtained with an optical flow algorithm. A strain pattern is then derived from the motion field. In experiments with 30 subjects, results indicate that strain pattern is an useful biometric, especially when dealing with extreme conditions such as shadow light and face camouflage, for which conventional face recognition methods are expected to fail. The ability to characterize the face using the elastic properties of facial skin opens up newer avenues to the face recognition community in the context of modeling a face using features beyond visible cues.

The purpose of this study was to determine the impact of an Instructor Effectiveness Course designed specifically to retain adjunct faculty and improve their overall success in teaching. The study also investigated the "online" and "face-to-face" groups of the Instructor Effectiveness Course and compared faculty who take this course to those who do not in order to detect any significant differences. Differences were measured through students' class grade point averages, (GPA's), and course completion rates for the three groups of faculty, as well as through the faculty performance on student evaluations. This mixed method, causal/comparative study looked at the adjunct faculty members who have taken the Instructor Effectiveness Course at a large southern community college compared to those who have not taken the course. This large southern community college employs approximately 1,400 adjunct faculty members. Four hundred of these adjunct faculty members have completed the Instructor Effectiveness Course offered at the college. For the past couple of years, the course has been offered both face-to-face and online. These adjunct faculty members teach both in the associate of arts (A.A.) programs, as well as the associate of science (A.S.) programs. The adjunct faculty members were divided into four groups: by those with less than one year of teaching experience, those with one year of teaching experience, those with two years of teaching experience, and those with three years of teaching experience. The adjunct faculty members were also divided by those teaching A.S. courses and those teaching A.A. courses, and by those teaching night and day classes. The adjunct faculty members with prior teaching experience who have been exempted from taking the course were not included in the study. The adjunct faculty members who had never taken the Instructor Effectiveness Course had significantly higher class GPA's than those who had taken the course onlin e or face-to-face. Student evaluations showed that adjunct faculty members who had completed the online version of the Instructor Effectiveness Course had a higher weighted average for all questions than those who had not taken the course. This study had three major objectives. The first was to investigate adjunct faculty members' retention rates. The second was to investigate students' success as measured by GPA and course completion. The third was to investigate adjunct faculty members' success as measured by students' evaluations. The research questions, hypotheses, participants, instrumentation, data collection, and data analysis have been provided in this chapter. The participants have been identified, and the rationale for their selection was described. The community college used as the research institution has been identified.

The pro-sociality of humans is manifested by the existence of cooperation in levels not common with any other species. Previous studies suggest that snap judgements of individuals are enough to determine if someone is a potential partner for cooperation. In addition to the often studied facial characteristics affecting cooperativeness and trustworthiness attribution (kin resemblance; attractiveness and emotional expression), the experimental work reported here examined the influence of head posture; gaze direction and skin colour on the attribution of trustworthiness and cooperation. A slightly tilted head (less than 3° downward) increased the perception of cooperativeness, especially for male and hostile looking faces. The importance of head tilt increased with decreased self-assessed dominance. Furthermore, even though some evidence that the effect of head posture is independent of gaze direction was found, gaze direction was also a strong indicator of cooperative intentions. Direct gaze and gaze slightly looking down (3°) were perceived as more cooperative than deviations of gaze outside this range (3° up or 6°- 9° down). Skin colour, a putative cue to current health status, was also found to impact on trustworthiness perception with a healthy skin colour increasing trustworthiness ratings. Additionally, as cooperative and trust decisions are vital for survival and social interactions, decisions based on facial appearance are made quickly and automatically as demonstrated by a trustworthiness modulation on an early face related component with 170 ms of exposure. Collectively, these findings suggest that facial characteristics employed to infer trust and cooperativeness help the observer to assess the motives and intentions of the individuals and assist the choice of partners that will lead to increased benefits and reduced costs in collaborative actions. Such considerations fit well with the evolutionary theory of cooperation as reciprocated social exchange.

Despite decades of effort in academia and industry, it is not yet possible to build machines that can replicate many seemingly-basic human perceptual abilities. This work focuses on the problem of face identification that most of us effortlessly solve daily. Substantial progress has been made towards the goal of automatically identifying faces under tightly controlled conditions; however, in the domain of unconstrained face images, many challenges remain. We observe that the recent combination of widespread digital photography, inexpensive digital storage and bandwidth, and online social networks has led to the sudden creation of repositories of billions of shared photographs and opened up an important new domain for unconstrained face identification research. Drawing upon the newly-popular phenomenon of “tagging,” we construct some of the first face identification datasets that are intended to model the digital social spheres of online social network members, and we examine various qualitative and quantitative properties of these image sets. The identification datasets we present here include up to 100 individuals, making them comparable to the average size of members’ networks of “friends” on a popular online social network, and each individual is represented by up to 100 face samples that feature significant real-world variation in appearance, expression, and pose. We demonstrate that biologically-inspired visual representations can achieve state-of-the-art face identification performance on our novel frontal and multi-pose face datasets. We also show that the addition of a tree-structured classifier and training set augmentation can enhance accuracy in the multi-pose setting. Finally, we illustrate that the machine-readable “social context” in which shared photos are often embedded can be applied to further boost face identification accuracy. Taken together, our results suggest that accurate automated face identification in vast online shared photo collections is now feasible. / Engineering and Applied Sciences

Automatic face recognition has attracted the attention of many research institutes, commercial industries, and government agencies in the past few years mainly due to the emergence of numerous applications, such as surveillance, access control to secure facilities, and airport screening. Almost all of the research on the early days of face recognition was focused on using 2-D (intensity/portrait) images of the face. While several sophisticated 2-D solutions have been proposed, unbiased evaluation studies show that their collective performance remains unsatisfactory, and degrades significantly with variations in lighting condition, face position, makeup, or existence of non-neutral facial expressions. Recent developments in 3-D imaging technology has made cheaper, quicker and more reliable acquisition of 3-D facial models a reality. These 3-D facial models contain information about the anatomical structure of the face that remains constant under variable lighting conditions, facial makeup, and pose variations. Thus, researchers are considering to utilize 3-D structure of the face alone or in combination with 2-D information to alleviate inherent limitations of 2-D images and attain better performance. Published 3-D face recognition algorithms have demonstrated promising results confirming the effectiveness of 3-D facial models in dealing with the above mentioned factors contributing to the failure of 2-D face recognition systems. However, the majority of these 3-D algorithms are extensions of conventional 2-D approaches, where intensity images are simply replaced by 3-D models rendered as range images. These algorithms are not specifically tailored to exploit abundant geometric and anthropometric clues available in 3-D facial models. In this dissertation we introduce innovative 3-D and 2-D+3-D facial measurements (features) that effectively describe the geometric characteristics of the corresponding faces. Some of the features described in this dissertation, as well as many features proposed in the literature are defined around or between meaningful facial landmarks (fiducial points). In order to reach our goal of designing an accurate automatic face recognition system, we also propose a novel algorithm combining 3-D (range) and 2-D (portrait) Gabor clues to pinpoint a number of points with meaningful anthropometric definitions with significantly better accuracies than those achievable using a single modality alone. This dissertation is organized as follows. In Chapter 1, various biometric modalities are introduced and the advantages of the facial biometrics over other modalities are discussed. The discussion in Chapter 1 is continued with introduction of the face recognition’s modes of operation followed by some current and potential future applications. The problem statement of this dissertation is also included in this chapter. In Chapter 2, an extensive review of the successful 2-D, 3-D, and 2-D+3-D face recognition algorithms are provided. Chapter 3 presents the details of our innovative 3-D and 2-D+3-D face features, as well as our accurate fiducial point detection algorithm. Conclusions and directions for future extensions are presented in Chapter 4. / text

Scholars have described conflict tactics as a means to engage or avoid a conflict, and face tactics as a means of face-saving by way of defense or restoration. While theories of conflict and face flourish, few researchers have sought an explanation of conflict themes within the field of nursing or examined how nurses display face-saving tactics within their conflict interactions. The goal of this study is to identify the connection of these concepts through a qualitative analysis of conflict stories compiled from interviews with licensed floor-nurses. The data is analyzed two ways: first, as conflict themes in stories about nurses’ floor/shift work; and secondly, as communicative face tactics used in conjunction with conflict styles as viewed through a nurses’ conflict-interaction. The study identified three outcomes. From the analysis of conflict stories, an updated and extended view of conflict themes in nursing is developed. Specific face tactics surfaced within certain conflict themes supporting the concept that face tactics can directly affect the outcome of a conflict interaction. And lastly, the discovery of new restorative and defensive face tactics not previously identified in research literature. The implications for theory and practical application are also discussed, as is the proposed direction for future research. / text

Knowledge is the critical success factor for organizations to compete in the contemporary business world. Organizations that can make full use of their collective expertise and knowledge are likely to be more innovative, efficient and effective in the marketplace. With the development of advanced information and communication technology, organizations are undertaking various knowledge management initiatives to augment traditional ways of knowledge transfer. This dissertation intended to understand how various factors influence knowledge workers' knowledge sourcing behavior in the multimodal knowledge network. More specifically, our research question is: How do task characteristics, knowledge characteristics and individual characteristics influence knowledge workers' channel preferences during their knowledge sourcing activities?We built a knowledge sourcing preference model which predicts knowledge workers' preferences among various knowledge channels. We identified eight important antecedents from a wide spectrum of task characteristics, knowledge characteristics, and individual characteristics. We also identified three representative knowledge sourcing channels: face-to-face communication with colleagues, knowledge repositories, and discussion forums. We developed eight hypotheses on how each of the antecedent influence channel preferences.We tested our hypotheses through a survey we conducted in an international information technology company. Out of the eight hypotheses, the hypotheses on the influences from knowledge codifiability, knowledge volatility, extroversion/introversion dimension of the personality, and reciprocation wariness are supported. The hypotheses on the influences from task interdependency and task urgency are partially supported. The hypotheses on the influences from task routineness and expertise are not supported.This study furthers our understanding of knowledge workers' knowledge sourcing behavior in a multimodal knowledge network. The results of this study help organizations understand the advantages and disadvantages of various sourcing channels under certain circumstance of tasks, knowledge, and individuals. With this understanding, organizations will be able to have reasonable expectations on the utilization of knowledge transfer approaches, and to improve the effectiveness of the knowledge transfer initiatives. This will enable the organizations to cultivate environments or design systems to develop the types of channels to accommodate the preferences of knowledge workers with various combinations of tasks, knowledge and individual characteristics.

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The purpose of this investigation is to further an understanding of the spiral of silence theory as it functions within both face-to-face (FtF) and computer-mediated contexts. Computer-mediated communication (CMC is often touted for being an empowering medium as it affords its users anonymity. This finding could have an impact on whether the spiral of silence occurs within CMC. Previous studies have relied upon hypothetical scenarios and have established weak support for the theory. Despite this study’s utilization of a within-subjects experimental design, however, no significant differences in minority opinion holders’ fear of isolation were found. Similarly, no significant relationship was found between minority opinion holders’ attention paid to news and fear of isolation. In regards to both majority and minority opinion holders, no significant differences in perceptions of opinions expressed in either condition were found. Reasons for such unexpected findings, as well as strengths, limitations, and directions for future research are discussed.

This study examined advice interactions following infidelity. Participants (N = 213) completed a survey concerning an instance on infidelity and a subsequent advice interaction. Injured party perceptions of advice interactions were measured by examining advice messages, perceived face threat, and perceived face support, in addition to perceived effectiveness of the advice message. Results from this study showed no significant differences in perceived face threat, perceived face support, or advice effectiveness between different advice messages. Results also indicated both positive and negative face threat as negative predictors of advice effectiveness. While negative face support was a positive predictor of advice effectiveness, positive face support was a negative predictor. When controlling for relational closeness, negative face support was the only significant predictor of advice effectiveness.