Sri International

Quang-Tuan Luong

Gregory Kent Myers

Robert C Bolles

James A Herson

Pascal Fua

Yvan G LeClerc

An apparatus and a concomitant method for detecting and recognizing text information in a captured imagery. The present method transforms the image of the text to a normalized coordinate system before performing OCR, thereby yielding more robust recognition performance. The present invention also combines OCR results from multiple frames, in a manner that takes the best recognition results from each frame and forms a single result that can be more accurate than the results from any of the individual frames.

Method and apparatus for recognizing text in an image sequence of scene imagery

The present invention provides a method for reliably detecting change in the 3-D shape of objects. It uses an estimate of the accuracy of the 3-D models derived from a set of images taken simultaneously. This accuracy estimate is used to distinguish between significant and insignificant changes in 3-D models derived from different image sets. In one embodiment of the present invention, the accuracy of the 3-D model is estimated using self-consistency methodology for estimating the accuracy of computer vision algorithms. In another embodiment of the present invention, resampling theory is used to compare the mean or median elevation for each change in the models. This methodology allows for estimating, for a given 3-D reconstruction algorithm and class of scenes, the expected variation in the 3-D reconstruction of objects as a function of viewing geometry and local image-matching quality (referred to as a 'score'). Differences between two 3-D reconstructions of an object that exceed this expected variation for a given significance level are deemed to be due to a change in the object's shape, while those below this are deemed to be due to uncertainty in the reconstructions.

Method and system for detecting changes in three dimensional shape

The present invention provides a method for measuring the self-consistency of inference algorithms. The present invention provides a method for measuring the accuracy of an inference algorithm that does not require comparison to ground truth. Rather, the present invention pertains to a method for measuring the accuracy of an inference algorithm by comparing the outputs of the inference algorithm against each other. Essentially, the present invention looks at how well the algorithm applied to many of the different observations gives the same answer. In particular, the present invention provides a method that is not time and labor intensive and is cost effective.

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Menlo Park, CA, United States of America

Quang-Tuan Luong