Abstract: A system and method for finding edge orientation and magnitude, and extracting a road path from an image. An image is segmented into at least a first window and a second window. A first road segment having plural parameters within the first window is specified. Plural road segments are identified, each having plural parameters, in the second window. The orientation of plural line segments in the second window are determined, and paired, based on their orientation. The line segment orientations are determined by receiving a plurality of edge orientation estimates, transforming a portion of them, and aggregating the transformed portion into an edge orientation estimate. A stochastic process is performed on the plural parameters of the plural road segments to identify a second road segment having the maximum correlation with the plural parameters of the first road segment.

Abstract: A system for generating three-dimensional models from still imagery or video streams from uncalibrated views, is presented. The system comprises a computer system including a processor, a memory coupled with the processor, an input coupled with the processor for receiving imagery captured from multiple pan-tilt settings of an uncalibrated image capturing device, and an output coupled with the processor for outputting an overall three-dimensional model of a complex scene containing rigid and non-rigid objects. The computer system includes a method for forming a three-dimensional model from uncalibrated views of an object, and a method for automatically stitching together three-dimensional models extracted from uncalibrated views of uncalibrated image capturing device locations, without the need of manual “image registration” of “points in common” between the models.

Abstract: The present invention provides an image and video indexing scheme for content analysis. According to the invention, a database of images or videos is compressed. By examining patterns in the compression scheme of each image or video, the present invention identifies the content of the data. In one embodiment, an unsupervised learning method is employed where each image or video is sub-divided into smaller blocks (8 pixels×8 pixels, for instance) and each of the smaller blocks is examined for its compression pattern. Then, the patterns associated with each of the smaller blocks is recorded for each of the images in the database and content is retrieved from the database by associating certain patterns or groups of patterns with certain content.

Abstract: A method of automatically recognizing text. The text is divided into whole words which are each recognize. Each whole word is characterized according to its silhouette. The silhouette is characterized by features in the silhouette such as upwardly extending “polls” and downwardly extending “holes”. The silhouette may also be characterized by its first syllable blends. Numbers are assigned to each of the different characteristics, and numbers may also be assigned based on analysis of a database of different kinds of cursive words. Recognition may be automatically carry out prior recognizing system which recognizes in this way.

Abstract: A system for automatically extracting geospatial features from multi-spectral imagery, suitable for fast and robust extraction of landmarks, is presented. The system comprises a computer system including a processor, a memory coupled with the processor, an input coupled with the processor for receiving imagery and user-provided geospatial features, and an output coupled with the processor for outputting the extracted landmarks. The computer system includes a region-growing system, an appending disjointed regions system, and an automatic reseeding system, which are configured to accurately and efficiently extract all regions within the input image that closely resemble the desired geospatial feature. The region-growing system is based on a level set technique, which allows for the fast and accurate extraction of a region evolved from a single user-provided seed point.

Abstract: A system for generating three-dimensional models from still imagery or video streams from uncalibrated views, is presented. The system comprises a computer system including a processor, a memory coupled with the processor, an input coupled with the processor for receiving imagery captured from multiple pan-tilt settings of an uncalibrated image capturing device, and an output coupled with the processor for outputting an overall three-dimensional model of a complex scene containing rigid and non-rigid objects. The computer system includes a method for forming a three-dimensional model from uncalibrated views of an object, and a method for automatically stitching together three-dimensional models extracted from uncalibrated views of uncalibrated image capturing device locations, without the need of manual “image registration” of “points in common” between the models.

Abstract: A system and method for finding edge orientation and magnitude, and extracting a road path from an image. An image is segmented into at least a first window and a second window. A first road segment having plural parameters within the first window is specified. Plural road segments are identified, each having plural parameters, in the second window. The orientation of plural line segments in the second window are determined, and paired, based on their orientation. The line segment orientations are determined by receiving a plurality of edge orientation estimates, transforming a portion of them, and aggregating the transformed portion into an edge orientation estimate. A stochastic process is performed on the plural parameters of the plural road segments to identify a second road segment having the maximum correlation with the plural parameters of the first road segment.

Abstract: The present invention provides an image and video indexing scheme for content analysis. According to the invention, a database of images or videos is compressed. By examining patterns in the compression scheme of each image or video, the present invention identifies the content of the data. In one embodiment, an unsupervised learning method is employed where each image or video is sub-divided into smaller blocks (8 pixels×8 pixels, for instance) and each of the smaller blocks is examined for its compression pattern. Then, the patterns associated with each of the smaller blocks is recorded for each of the images in the database and content is retrieved from the database by associating certain patterns or groups of patterns with certain content.

Abstract: A method of automatically recognizing text. The text is divided into whole words which are each recognize. Each whole word is characterized according to its silhouette. The silhouette is characterized by features in the silhouette such as upwardly extending “polls” and downwardly extending “holes”. The silhouette may also be characterized by its first syllable blends. Numbers are assigned to each of the different characteristics, and numbers may also be assigned based on analysis of a database of different kinds of cursive words. Recognition may be automatically carry out prior recognizing system which recognizes in this way.

Abstract: The present invention provides an image and video indexing scheme for content analysis. According to the invention, a database of images or videos is compressed. By examining patterns in the compression scheme of each image or video, the present invention identifies the content of the data. In one embodiment, an unsupervised learning method is employed where each image or video is sub-divided into smaller blocks (8 pixels×8 pixels, for instance) and each of the smaller blocks is examined for its compression pattern. Then, the patterns associated with each of the smaller blocks is recorded for each of the images in the database and content is retrieved from the database by associating certain patterns or groups of patterns with certain content.