Thesis (M.A.)--Bowling Green State University, 2009. / Document formatted into pages; contains xi, 122 p. Includes bibliographical references.

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This thesis is concerned with the problem of place recognition for mobile robots. How can a robot determine its location from an image or sequence of images, without any prior knowledge of its position, even in a world where many places look identical? We outline a new probabilistic approach to the problem, which we call Fast Appearance Based Mapping or FAB-MAP. Our map of the environment consists of a set of discrete locations, each with an associated appearance model. For every observation collected by the robot, we compute a probability distribution over the map, and either create a new location or update our belief about the appearance of an existing location. The technique can be seen as a new type of SLAM algorithm, where the appearance of locations (rather than their position) is subject to estimation. Unlike existing SLAM systems, our appearance based technique does not rely on keeping track of the robot in any metric coordinate system. Thus it is applicable even when informative observations are available only intermittently. Solutions to the loop closure detection problem, the kidnapped robot problem and the multi-session mapping problem arise as special cases of our general approach. Abstract Our probabilistic model introduces several technical advances. The model incorporates correlations between visual features in a novel way, which is shown to improve system performance. Additionally, we explicitly compute an approximation to the partition function in our Bayesian formulation, which provides a natural probabilistic measure of when a new observation should be assigned to a location not already present in the map. The technique is applicable even in visually repetitive environments where many places look the same. Abstract Finally, we define two distinct approximate inference procedures for the model. The first of these is based on concentration inequalities and has general applicability beyond the problem considered in this thesis. The second approach, built on inverted index techniques, is tailored to our specific problem of place recognition, but achieves extreme efficiency, allowing us to apply FAB-MAP to navigation problems on the largest scale. The thesis concludes with a visual SLAM experiment on a trajectory 1,000 km long. The system successfully detects loop closures with close to 100% precision and requires average inference time of only 25 ms by the end of the trajectory.

Thesis (M.S.)--University of Texas at Dallas, 2007. / Includes vita. Includes bibliographical references (leaves 38-41)

This study designed and implemented an appearance-based skin cancer prevention intervention in college-aged females. One hundred and forty-seven respondents were randomly assigned to treatment or control groups. Treatment respondents received a short workbook describing the appearance damaging effects of indoor tanning. At short-term follow-up (2 weeks later) treatment respondents had significantly more negative attitudes toward indoor tanning, and reported fewer intentions to indoor tan. At 2-month follow-up, treatment respondents reported indoor tanning one-half as much as control respondents in the previous 2 months. This appearance-based intervention was able to produce clinically significant changes in indoor tanning use tendencies that could have a beneficial effect on the future development of skin cancer.

Although humanoid robots are being designed to assist people in various tasks, there remain gaps in our understanding of the perceptions that humanoid faces evoke in the user. Understanding user perceptions would help design robots that are better suited for the target user group. Younger and older adults’ preferences for robot appearance were assessed out of three levels of human-likeness. In general, people perceived a mixed human-robot appearance less favorably compared to highly human and highly robotic appearances. Additionally the nature of task also influenced people’s overall perceptions of robots. Robots were most positively evaluated for assistance with chores and less positively for personal care and decision-making. Moreover, task and robot humanness had an interactive effect on people’s likability, trust, and perceived usefulness toward robots. Age-related differences in preferences of robot humanness were also observed. Older adults showed a higher inclination toward human-looking appearance of robots whereas younger adults’ preferences were more distributed across the levels of humanness. An appearance with mixed human-robot features was more likely to be rejected by older adults than by younger adults, and the difference was most striking for a decision-making task. Besides the humanness of the robot face, perceptions of robot appearances were also influenced by factors such as robot gender, specific facial features/aesthetics, expressiveness, perceived personality, and perceived capability. Future studies should measure the relative weight of these different factors in the formation of perceptions, both at a global level and at a task-specific level.

Thesis (M.A.)--West Virginia University, 2001. / Title from document title page. Document formatted into pages; contains v, 35 p. Includes abstract. Includes bibliographical references (p. 26-31).

The purpose of this study was to discover whether the gymnasts' body shape affects the judging of gymnastics. The goal was to discover whether the judges' perceptions of the gymnasts' body shape related to the gymnasts' performance scores. A second goal was to discover whether performance scores differed when given by judges with two levels of experience (experienced and novice). Videotapes of compulsory routines performed by 16 gymnasts on bars, beam and floor were constructed to simulate a competition. Eighteen judges, nine novice and nine experienced, evaluated the routines. They were also required to rate their perception of the aesthetic appeal of the 16 gymnasts' body shape. Each gymnasts' body mass index (BMI) was calculated from their height and weight measurements to quantify body shape. The scores were analyzed using repeated measures analysis of variance. The results showed a significant main effect of BMI on judges' perception of gymnasts' body shape scores, $F(3,48)=9.50, p<.001.$ Gymnasts with a medium-low BMI received significantly higher perception scores than gymnasts with a medium-high BMI and gymnasts with a high BMI. The results also showed a significant main effect $(p<.001)$ of BMI on performance scores. Gymnasts with a high BMI received higher performance scores than those gymnasts with a low BMI, medium-low BMI and medium-high BMI. The effect of judge experience was very close to significant $(p<.059)$ in relation to performance scores. Experienced judges gave lower performance scores than novice judges. Although all judges preferred smaller body shape, this preference did not affect the performance scores award by the judges.

Thesis (M.S.W.)--Smith College School for Social Work, Northampton, Mass., 2009. / Includes bibliographical references (p. 86-87).

Thesis (M.S.)--Springfield College, 2002. / Includes bibliographical references.