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Typescript (photocopy) / Bibliography: leaves 82-88. / Microfiche. / ix, 88 leaves, bound ill. 28 cm

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Thesis (Ph.D.)--Computing, Georgia Institute of Technology, 2009. / Committee Chair: Rehg, James M.; Committee Co-Chair: Bobick, Aaron; Committee Member: Balch, Tucker; Committee Member: Christensen, Henrik I.; Committee Member: Pietro Perona

Thesis (Ph. D.)--University of Hong Kong, 2000. / Includes bibliographical references (leaves 90-95).

Thesis (Ph. D.)--University of Texas at El Paso, 2009. / Title from title screen. Vita. CD-ROM. Includes bibliographical references. Also available online.

Thesis (M.S.)--State University of New York at Binghamton, Department of Psychology, 2008. / Includes bibliographical references.

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The goal of this dissertation was to bridge the gap between perceptual learning theory and training application. Visual perceptual skill has been a vexing topic in training science for decades. In complex task domains, from aviation to medicine, visual perception is critical to task success. Despite this, little, if any, emphasis is dedicated to developing perceptual skills through training. Much of this may be attributed to the perceived inefficiency of perceptual training. Recent applied research in perceptual training with discrimination training, however, holds promise for improved perceptual training efficiency. As with all applied research, it is important to root application in solid theoretical bases. In perceptual learning, the challenge is connecting the basic science to more complex task environments. Using a common aviation task as an applied context, participants were assigned to a perceptual training condition based on variation of image complexity and training type. Following the training, participants were tested for transfer of skill. This was intended to help to ground a potentially useful method of perceptual training in a model category learning, while offering qualitative testing of model fit in increasingly complex visual environments. Two hundred and thirty-one participants completed the computer based training module. Results indicate that predictions of a model of category learning largely extend into more complex training stimuli, suggesting utility of the model in more applied contexts. Although both training method conditions showed improvement across training blocks, the discrimination training condition did not transfer to the post training transfer tasks. Lack of adequate contextual information related to the transfer task in training was attributed to this outcome. Further analysis of the exposure training condition showed that iv individuals training with simple stimuli performed as well as individuals training on more complex stimuli in a complex transfer task. On the other hand, individuals in the more complex training conditions were less accurate when presented with a simpler representation of the task in transfer. This suggests training benefit to isolating essential task cues from irrelevant information in perceptual judgment tasks. In all, the study provided an informative look at both the theory and application associated with perceptual category learning. Ultimately, this research can help inform future research and training development in domains where perceptual judgment is critical for success.