Abstract: A method and system that utilizes an admissible heuristic to determine the fastest-path between two points on a road map is disclosed. The method and system are based in part on a set of separators disposed on the map and represented by line segments, either independent or organized into hierarchical tree structures and based on recursive spatial subdivision. A preprocessing step computes a vector of values per road junction based on the separators that is then stored with the map and used to efficiently compute a high-quality heuristic to be used at a query stage. The heuristic scales well to any map size, resulting in a very efficient determination of fastest-path queries between points at all distances. The implementation is economically feasible and the resulting query speeds are significantly faster than other known heuristics and other state-of-the-art systems used for computing fastest-paths on maps.

Abstract: Described in detail herein is a method for encrypting or encoding time-stamped location data associated with a computing device. The method converts time and location information associated with the computing device into a vector format. The method generates a code vector based on the converted time and location vector. The method sorts entries in the code vector based at least in part on a predetermined ordering scheme. The method executes a random modification to each of the sorted entries. The method compares the code vector to at least one other code vector associated with another computing device. The method identifies other code vectors within a specified distance of the given code vector. The method concludes that the computing device and the at least one other computing device were in proximity to each other during a time period corresponding to the time information.

Abstract: Described in detail herein is a method for encrypting or encoding time-stamped location data associated with a computing device. The method converts time and location information associated with the computing device into a vector format. The method generates a code vector based on the converted time and location vector. The method sorts entries in the code vector based at least in part on a predetermined ordering scheme. The method executes a random modification to each of the sorted entries. The method compares the code vector to at least one other code vector associated with another computing device. The method identifies other code vectors within a specified distance of the given code vector. The method concludes that the computing device and the at least one other computing device were in proximity to each other during a time period corresponding to the time information.

Abstract: A method and system that utilizes an admissible heuristic to determine the fastest-path between two points on a road map is disclosed. The method and system are based in part on a set of separators disposed on the map and represented by line segments, either independent or organized into hierarchical tree structures and based on recursive spatial subdivision. A preprocessing step computes a vector of values per road junction based on the separators that is then stored with the map and used to efficiently compute a high-quality heuristic to be used at a query stage. The heuristic scales well to any map size, resulting in a very efficient determination of fastest-path queries between points at all distances. The implementation is economically feasible and the resulting query speeds are significantly faster than other known heuristics and other state-of-the-art systems used for computing fastest-paths on maps.

Abstract: A method for image processing in video conferencing, for correcting the gaze of an interlocutor in an image or a sequence of images captured by at least one real camera, comprises the steps of the at least one real camera acquiring an original image of the interlocutor; synthesizing a corrected view of the interlocutor's face as seen by a virtual camera, the virtual camera being located on the interlocutor's line of sight and oriented towards the interlocutor; transferring the corrected view of the interlocutor's face from the synthesized view into the original image, thereby generating a final image; at least one of displaying the final image and transmitting the final image.

Abstract: A method for image processing in video conferencing, for correcting the gaze of an interlocutor in an image or a sequence of images captured by at least one real camera, comprises the steps of the at least one real camera acquiring an original image of the interlocutor; synthesizing a corrected view of the interlocutor's face as seen by a virtual camera, the virtual camera being located on the interlocutor's line of sight and oriented towards the interlocutor; transferring the corrected view of the interlocutor's face from the synthesized view into the original image, thereby generating a final image; at least one of displaying the final image and transmitting the final image.

Abstract: A method of remotely viewing a video from a selected viewpoint selected by the viewer from a continuous segment, including, receiving a recording of a video of a subject recorded using a first depth video camera that records a video comprising a sequence of picture frames and additionally records a depth value for pixels of the picture frames; receiving a recording of a video of the subject recorded using a standard video camera or a second depth video camera positioned to record a video at a viewpoint that differs from the viewpoint of the depth video camera; using the recordings to render a viewable video from the selected viewpoint; and display the rendered viewable video to the viewer.

Abstract: A method of remotely viewing a video from a selected viewpoint selected by the viewer from a continuous segment, including, recording a video of a subject using at least one depth video camera that records a video comprising a sequence of picture frames and additionally records a depth value for each pixel of the picture frames, recording a video of the subject using at least one standard video camera positioned to record a video at a viewpoint that differs from the viewpoint of the depth video camera, rendering a depth hull that defines a three dimensional outline of the subject being recorded using the depth values recorded by the depth video cameras, providing the recorded video from one or more cameras positioned on either side of the selected viewpoint, incorporating the recorded video from the one or more cameras onto the rendered depth hull to render a viewable video from the selected viewpoint; and displaying the rendered viewable video to the viewer.

Abstract: Certain exemplary embodiments comprise a method, comprising: in a sensor node network comprising a plurality of sensor nodes, each sensor node from the plurality of sensor nodes having location coordinates that are initially unknown, each sensor node from the plurality of sensor nodes having neighbors, each sensor node from the plurality of sensor nodes capable of determining distances only to that sensor node's neighbors: for each sensor node from the plurality of sensor nodes, communicating with that sensor node's neighbors; and based only on communications between neighbors, in a fully distributed manner, generating a sensor node network layout that indicates the location coordinates of each sensor node.

Abstract: A method and system for sensor network localization including communicating with a plurality of directly neighboring sensor nodes to determine a patch in a sensor network, localizing the patch, generating a system of equations from computed local coordinates of the patch, incorporating global coordinates of a plurality of sensor nodes into the system of equations, and solving the equations using a distributed equation solver is described. The described methods and systems have utility in the arts of military, radio, police, fire, rescue, business, travel, and other diverse applications.

Abstract: A method of remotely viewing a video from a selected viewpoint selected by the viewer from a continuous segment, including, recording a video of a subject using at least one depth video camera that records a video comprising a sequence of picture frames and additionally records a depth value for each pixel of the picture frames, recording a video of the subject using at least one standard video camera positioned to record a video at a viewpoint that differs from the viewpoint of the depth video camera, rendering a depth hull that defines a three dimensional outline of the subject being recorded using the depth values recorded by the depth video cameras, providing the recorded video from one or more cameras positioned on either side of the selected viewpoint, incorporating the recorded video from the one or more cameras onto the rendered depth hull to render a viewable video from the selected viewpoint; and displaying the rendered viewable video to the viewer.

Abstract: Certain exemplary embodiments comprise a method, comprising: in a sensor node network comprising a plurality of sensor nodes, each sensor node from the plurality of sensor nodes having location coordinates that are initially unknown, each sensor node from the plurality of sensor nodes having neighbors, each sensor node from the plurality of sensor nodes capable of determining distances only to that sensor node's neighbors: for each sensor node from the plurality of sensor nodes, communicating with that sensor node's neighbors; and based only on communications between neighbors, in a fully distributed manner, generating a sensor node network layout that indicates the location coordinates of each sensor node.

Abstract: Certain exemplary embodiments comprise a method, comprising: in a sensor node network comprising a plurality of sensor nodes, each sensor node from the plurality of sensor nodes having location coordinates that are initially unknown, each sensor node from the plurality of sensor nodes having neighbors, each sensor node from the plurality of sensor nodes capable of determining distances only to that sensor node's neighbors: for each sensor node from the plurality of sensor nodes, communicating with that sensor node's neighbors; and based only on communications between neighbors, in a fully distributed manner, generating a sensor node network layout that indicates the location coordinates of each sensor node.

Abstract: This disclosure provides a system for classifying images, used in image detection, image recognition, or other computer vision. The system processes directory images to obtain eigenvectors and eigenvalues, and selects a set of “smooth” basis vectors formed by linear combinations of these eigenvectors to be applied against a target image. Contrary to conventional wisdom, however, a group of the eigenvectors having the weakest eigenvalues are used to select the basis vectors. A second process is then performed on this group of “weakest” eigenvectors to identify a set of candidate vectors, ordered in terms of “smoothness.” The set of basis vectors (preferably 3-9) is then chosen from the candidate vectors in order of smoothness, which are then applied in an image detection or image recognition process.

Abstract: This disclosure provides a system for classifying images, used in image detection, image recognition, or other computer vision. The system processes directory images to obtain eigenvectors and eigenvalues, and selects a set of “smooth” basis vectors formed by linear combinations of these eigenvectors to be applied against a target image. Contrary to conventional wisdom, however, a group of the eigenvectors having the weakest eigenvalues are used to select the basis vectors. A second process is then performed on this group of “weakest” eigenvectors to identify a set of candidate vectors, ordered in terms of “smoothness.” The set of basis vectors (preferably 3-9) is then chosen from the candidate vectors in order of smoothness, which are then applied in an image detection or image recognition process.

Abstract: This disclosure provides a system for classifying images, used in image detection, image recognition, or other computer vision. The system processes directory images to obtain eigenvectors and eigenvalues, and selects a set of “smooth” basis vectors formed by linear combinations of these eigenvectors to be applied against a target image. Contrary to conventional wisdom, however, a group of the eigenvectors having the weakest eigenvalues are used to select the basis vectors. A second process is then performed on this group of “weakest” eigenvectors to identify a set of candidate vectors, ordered in terms of “smoothness.” The set of basis vectors (preferably 3-9) is then chosen from the candidate vectors in order of smoothness, which are then applied in an image detection or image recognition process.

Abstract: A method for compressing a mesh having a plurality of vertices, each vertex characterized by a degree equal to the number of edges incident thereon, including arranging substantially all of the vertices in a consecutive order, generating a topology list including the degrees of the vertices in the consecutive order, and providing a coded stream of signals including the topology list.