An Analysis of the Effect of Gaussian Error in Object Recognition

Title: en_US An Analysis of the Effect of Gaussian Error in Object Recognition
Creator: en_US Sarachik, Karen Beth
Date: 2004-10-20T20:24:12Z
Date Available: 2004-10-20T20:24:12Z
Date Issued: en_US 1994-02-01
Identifier: en_US AITR-1469
uri: http://hdl.handle.net/1721.1/7057
Abstract: en_US Object recognition is complicated by clutter, occlusion, and sensor error. Since pose hypotheses are based on image feature locations, these effects can lead to false negatives and positives. In a typical recognition algorithm, pose hypotheses are tested against the image, and a score is assigned to each hypothesis. We use a statistical model to determine the score distribution associated with correct and incorrect pose hypotheses, and use binary hypothesis testing techniques to distinguish between them. Using this approach we can compare algorithms and noise models, and automatically choose values for internal system thresholds to minimize the probability of making a mistake.
Extent: 7376380 bytes; 3521585 bytes
Format: application/postscript; application/pdf
Language: en_US
Relation: en_US AITR-1469