This research project is a study of the role of fixation and visual attention in object recognition. In this project, we build an active vision system which can recognize a target object in a cluttered scene efficiently and reliably. Our system integrates visual cues like color and stereo to perform figure/ground separation, yielding candidate regions on which to focus attention. Within each image region, we use stereo to extract features that lie within a narrow disparity range about the fixation position. These selected features are then used as input to an alignment-style recognition system. We show that visual attention and fixation significantly reduce the complexity and the false identifications in model-based recognition using Alignment methods. We also demonstrate that stereo can be used effectively as a figure/ground separator without the need for accurate camera calibration.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/6775 |
| Date | 21 July 1995 |
| Creators | Ratan, Aparna Lakshmi |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | en_US |
| Detected Language | English |
| Format | 97 p., 8826773 bytes, 2714320 bytes, application/postscript, application/pdf |
| Relation | AITR-1529 |
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