Abstract: A method is disclosed. The method receives a two dimensional or a three dimensional computer generated representation of an area, receives a plurality of images of the area captured by one or more video cameras, detects a first moving object in the plurality of images, generates a computer representation of the first moving object, correlates the images of the area captured by the one or more video cameras with the two dimensional or three dimensional computer generated representation of the area, and displays the computer representation of the first moving object in the two dimensional or the three dimensional computer generated representation of the area.

Abstract: A method and system for detection of contaminants present on a lens of an imaging device is disclosed. An input image received from an imaging device is split into a plurality of patches of predefined size and a kurtosis value calculated for each and compared with a median kurtosis value. Patches having kurtosis value less than the median kurtosis value are selected. Based on comparison of a first maximum likelihood of the selected patches with a predefined threshold, one or more selected patches are stored. Such patches are split into a top and a bottom portion for processing based on discrete wavelet transform and singular value decomposition, respectively. The top and the bottom portion are merged patches for which a second maximum likelihood is greater than a second predefined threshold, are stored. Further, contaminants in the image are classified into predefined categories based on one or more image features.

Abstract: A method and system for detection of contaminants present on a lens of an imaging device is disclosed. An input image received from an imaging device is split into a plurality of patches of predefined size and a kurtosis value calculated for each and compared with a median kurtosis value. Patches having kurtosis value less than the median kurtosis value are selected. Based on comparison of a first maximum likelihood of the selected patches with a predefined threshold, one or more selected patches are stored. Such patches are split into a top and a bottom portion for processing based on discrete wavelet transform and singular value decomposition, respectively. The top and the bottom portion are merged patches for which a second maximum likelihood is greater than a second predefined threshold, are stored. Further, contaminants in the image are classified into predefined categories based on one or more image features.

Abstract: A method and apparatus for identifying a target object. A group of objects is identified in an image. The group of objects provides a context for identifying the target object in the image. The target object is searched for in the image using the context provided by the group of objects.

Abstract: A method, system, and computer program product for detecting objects. Members of a general class of objects are searched for in a number of images. Members of a specific class of objects are searched for in a number of regions in the number of images where the number of regions contains at least a portion of the members of the general class. A member in the members of the specific class is a potential threat to a rotorcraft.

Abstract: A method and apparatus for processing images. A sequence of images for a scene is received from an imaging system. An object in the scene is detected using the sequence of images. A viewpoint of the imaging system is registered to a model of the scene using a region in the model of the scene in which an expected behavior of the object is expected to occur.

Abstract: A method of recognizing features in a 3D environment includes using a sensor that collects a plurality of sensed data points, populating a strip histogram grid having a plurality of strips, each strip having a dx dimension and a dy dimension, by assigning each sensed data point to a strip in the strip histogram grid that has x, y and z dimensions that encompass the spatial coordinate information of the respective assigned sensed data point, and estimating the local ground plane for a strip in the strip histogram grid by using information on each sensed data point assigned to that strip and surrounding strips in the strip histogram grid. Further methods include extracting smooth surfaces, building segmentation, top down segmentation and bottom up segmentation.

Abstract: A method, apparatus, and computer program product for tracking objects. A number of objects is detected in an image to form a number of detected objects. A number of previously identified objects is searched for in the image using a number of signatures for the number of previously identified objects. A number of tracks for the objects is updated using the number of detected objects and a number of reidentified objects. The number of reidentified objects is from searching for the number of previously identified objects.

Abstract: A method of extracting street and road data from a dataset obtained using LIDAR techniques to scan a terrestrial region of the earth's surface of interest to form the dataset. The method includes: converting the dataset into an implicit representation using a population function; converting the implicit representation into 2D point data which are supplied to an agglomerative Gaussian mixture decomposition module, the agglomerative Gaussian mixture decomposition module automatically and parsimoniously fitting the 2-D point data with a set of Gaussian components; and modeling a segment of a street grid in the dataset by Gaussian models and constraining the Gaussian models to align with each other and a dominant orientation of the streets in order to detect streets. Ray tracing techniques may be used to detect curbs and medians.

Abstract: A method and apparatus for processing images. Clusters of first features identified in a first image are identified. Each cluster in the clusters comprises a first group of features from the first features. A transformation for registering each cluster in the clusters with a corresponding cluster comprising a second group of features from second features identified in a second image is identified using an initial correspondence between the first features in the first image and the second features in the second image. A set of clusters from the clusters of the first features is identified using the transformation identified for each cluster. A final transformation for registering the first image with the second image is identified using the set of clusters.

Abstract: In an embodiment, a grammar-based, cueing method of object recognition is disclosed. The method may include or comprise accessing cells that define a portion of a three-dimensional (3-D) scene, assigning occupation parameters to the cells to define a plurality of occupied cells and at least one vacant cell, and assigning localization parameters to the occupied cells based on the occupation parameters of their respective neighboring cells. The method may further include or comprise characterizing a plurality of the occupied cells as geometric cues based on their respective occupation and localization parameters, and identifying a target geometric shape associated with the geometric cues.

Abstract: A method and apparatus for processing images. A sequence of images for a scene is received from an imaging system. An object in the scene is detected using the sequence of images. A viewpoint of the imaging system is registered to a model of the scene using a region in the model of the scene in which an expected behavior of the object is expected to occur.

Abstract: A method of recognizing geometrically salient objects from sensed data points collected in a 3D environment includes using a sensor that collects a plurality of sensed data points each having spatial coordinate information in three dimensions x, y and z, populating a strip histogram grid having a plurality of strips, each strip having a z, dx and dy dimensions, wherein dx is a portion of an x dimension and dy is a portion of a y dimension of the strip histogram grid, by assigning each sensed data point to a strip that has x, y and z dimensions that encompass the spatial coordinate information of the respective assigned sensed data point, and segmenting the strip histogram grid into a plurality of segmented regions, each segmented region comprising one strip or a group of neighboring strips having similar attributes.

Abstract: A method and apparatus for identifying a target object. A group of objects is identified in an image. The group of objects provides a context for identifying the target object in the image. The target object is searched for in the image using the context provided by the group of objects.

Abstract: A method and apparatus for processing images. Clusters of first features identified in a first image are identified. Each cluster in the clusters comprises a first group of features from the first features. A transformation for registering each cluster in the clusters with a corresponding cluster comprising a second group of features from second features identified in a second image is identified using an initial correspondence between the first features in the first image and the second features in the second image. A set of clusters from the clusters of the first features is identified using the transformation identified for each cluster. A final transformation for registering the first image with the second image is identified using the set of clusters.

Abstract: A video detection and monitoring method and apparatus utilizes an application-specific object based segmentation and recognition system for locating and tracking an object of interest within a number of sequential frames of data collected by a video camera or similar device. One embodiment includes a background modeling and object segmentation module to isolate from a current frame at least one segment of the current frame containing a possible object of interest, and a classification module adapted to determine whether or not any segment of the output from the background modeling apparatus includes an object of interest and to characterize any such segment as an object segment. An object segment tracking apparatus is adapted to track the location within a current frame of any object segment and to determine a projected location of the object segment in a subsequent frame.

Abstract: An apparatus and method provides application specific multidimensional information to an application running on a user computing device from a plurality of member documents electronically extracted from a library of electronically searchable documents. An information extractor is adapted to extract occurrences of prospective representations of dimensions of application specific multidimensional information and occurrences of non-application specific multidimensional information from the member documents. Also, an encoder is adapted to encode the occurrences of prospective dimensions of application specific and non-application specific multidimensional information contained in member documents. A member document identifier determines document formatting and decides whether to proceed with further processing. An information verification unit optionally verifies the extraction of application specific multidimensional information from the member documents.

Abstract: The present invention provides an improved method and system for training an on-line fuzzy inference network to generate a rule base, and a rule base generated thereby. Tuning and applying a learning rule to the fuzzy rules generated by the fuzzy inference network in such as manner as to divorce the performance of the network from the number of input dimensions allows the present invention to adapt a fuzzy inference network such as a SONFIN to be effective for the classification of high-dimensional data in problems requiring the use of a high number of dimensions such as occupant recognition in vehicles, weather forecasting, and economic forecasting.

Abstract: A vision-based system for automatically detecting the type of object within a specified area, such as the type of occupant within a vehicle. Determination of the type of occupant can then be used to determine whether an airbag deployment system should be enabled or not. The system extracts different features from images captured by image sensors. These features are then processed by classification algorithms to produce occupant class confidences for various occupant types. The occupant class confidences are then fused and processed to determine the type of occupant. In a preferred embodiment, image features derived from image edges, motion, and range are used. Classification algorithms may be implemented by using trained C5 decision trees, trained Nonlinear Discriminant Analysis networks, Hausdorff template matching and trained Fuzzy Aggregate Networks.

Abstract: An apparatus and method are disclosed for electronically extracting application specific multidimensional information from a library of electronically searchable documents, wherein at least one dimension of the information is a category, which may comprise an automatic document miner in communication with the contents of the library and adapted to electronically extract relevant documents from the library; an E-Space filter creator adapted to create from the extracted relevant documents a category specific representation of the extracted relevant documents comprising the E-Space filter; a document selector adapted to utilize the E-Space filter to separate the extracted relevant documents into member documents and non-member documents and to discard the non-member documents; and an application specific multidimensional information extractor adapted to extract occurrences of application specific multidimensional information from the member documents.