| dc.contributor |
Pawan Sinha. |
|
| dc.contributor |
Massachusetts Institute of Technology. Dept. of Brain and Cognitive Sciences. |
|
| dc.contributor |
Massachusetts Institute of Technology. Dept. of Brain and Cognitive Sciences. |
|
| dc.creator |
Balas, Benjamin J. (Benjamin John) |
|
| dc.date |
2007-09-28T13:31:03Z |
|
| dc.date |
2007-09-28T13:31:03Z |
|
| dc.date |
2007 |
|
| dc.date |
2007 |
|
| dc.identifier |
http://hdl.handle.net/1721.1/39004 |
|
| dc.identifier |
166569603 |
|
| dc.description |
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2007. |
|
| dc.description |
Includes bibliographical references. |
|
| dc.description |
The effects of observed object motion on object perception are examined in two sets of studies. The first section of the thesis provides a thorough examination of various untested aspects of the basic "temporal association" hypothesis, which suggests that object motion provides a principled basis for linking distinct images together if they appear within small time intervals. Using familiar and unfamiliar objects undergoing various forms of non-rigid motion, I ask how well this simple hypothesis predicts behavior in change detection and categorization tasks. The results favor a modified version of the hypothesis which operates over a population of units, such that increases in generalization also produce increases in image sensitivity. The observed effects of long-term knowledge concerning object appearance and expected patterns of motion also force additional modifications of the initial hypothesis to incorporate interactions between learned predictions and recent experience. Specifically, the tendency to alter patterns of generalization following dynamic exposure appears to be contingent on the stability of the direction of movement through appearance space. |
|
| dc.description |
(cont.) Consistent with this expanded model, performance in our categorization task appears to depend heavily on whether or not a coherent direction of movement through appearance space can be determined across both categories to be learned. In the second section of the thesis, I report the results of two parametric analyses of image encoding following dynamic exposure. In each case, I ask how the movement of an object up to the presentation of particular image affects an observers' ability to accurately recall that image. Novel, rigidly rotating objects are used in both cases to characterize the influence of appearance dynamics on short and long-term image encoding. In both cases, I find that local appearance change over time exerts a powerful influence on encoding, suggesting that both immediate percepts and visual memory are modulated by the recent past. The result is a complex picture of dynamic object perception that goes far beyond the basic principle of object motion as a tool for learning invariant recognition. |
|
| dc.description |
by Benjamin J. Balas. |
|
| dc.description |
Ph.D. |
|
| dc.format |
119 p. |
|
| dc.format |
application/pdf |
|
| dc.language |
eng |
|
| dc.publisher |
Massachusetts Institute of Technology |
|
| dc.rights |
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. |
|
| dc.rights |
http://dspace.mit.edu/handle/1721.1/7582 |
|
| dc.subject |
Brain and Cognitive Sciences. |
|
| dc.title |
Learning about dynamic objects and recognizing static form |
|
| dc.title |
Learning from dynamic objects and recognizing static form |
|
| dc.type |
Thesis |
|