Abstract: Method and system for measuring a relative position and orientation of range cameras using a movement of an object within a scene. In general, the method and system determine the relative pose between two cameras by measuring a path the movement of the object makes within a scene and calculating transformation parameters based on these measurements. These transformation parameters are used to determine the relative position of each camera with respect to a base camera. The system and method include other novel features, such as a data synchronization feature that uses a time offset between cameras to obtain the transformation parameters, and a technique that improves the robustness and accuracy of solving for the transformation parameters, and an interpolation process that interpolates between sampled points if there is no data at a particular instant in time.

Abstract: Method and system for measuring a relative position and orientation of range cameras using a movement of an object within a scene. In general, the method and system determine the relative pose between two cameras by measuring a path the movement of the object makes within a scene and calculating transformation parameters based on these measurements. These transformation parameters are used to determine the relative position of each camera with respect to a base camera. The system and method include other novel features, such as a data synchronization feature that uses a time offset between cameras to obtain the transformation parameters, and a technique that improves the robustness and accuracy of solving for the transformation parameters, and an interpolation process that interpolates between sampled points if there is no data at a particular instant in time.

Abstract: A system and method for maintaining a background model of an image sequence by processing on multiple spatial scales. These multiple spatial scales include a pixel scale, a regional scale and a frame scale. The image sequence undergoes pixel processing that determines a current background model and provides an initial pixel assignment as either a background or a foreground pixel. Region processing further refines the initial pixel assignments by considering relationships between pixels and possibly reassigning pixels. Frame processing further refines the current background model by determining whether a substantial change has occurred in the actual background and, if so, providing a more accurate background model.

Abstract: An object recognition system and process that identifies people and objects depicted in an image of a scene. In general, this system and process entails first creating model histograms of the people and objects that it is desired to identify in the image. Then, the image is segmented to extract regions which likely correspond to the people and objects being identified. A histogram is computed for each of the extracted regions, and the degree of similarity between each extracted region histogram and each of the model histograms is assessed. The extracted regions having a histogram that exhibits a degree of similarity to one of the model histograms which exceeds a prescribed threshold is designated as corresponding to the person or object associated with that model histogram.

Abstract: Methods and systems that determine automatically the likelihood that a device is inside or outside of a structure or building. The system uses one or more sensors to detect ambient conditions, and make the determination. The inference can be used to save power or suppress services from certain devices, which are irrelevant, cannot be used effectively, or do not function under certain circumstances. In support thereof, the system includes one or more context sensors that measure parameters associated probabilistically with the context of a device. A context computing component considers one or more context sensors and facilitates determination of ideal actions, policies, and situations associated with the device. A service provided by the subject invention is the inference from one or more available observations the probability that the device is inside versus outside.

Abstract: An architecture for minimizing calibration effort in an IEEE 802.11 device location measurement system. The calibration technique is based upon a regression function that produces adequately accurate location information as a function of signal strength regardless of gaps in the calibration data or minimally available data. The algorithm takes a set of signal strengths from known room locations in a building and generates a function giving (x,y) as a function of signal strength, which function may then be used for the estimation of new locations. Radial basis functions, which are simple to express and compute, are used for regression. The fact that the algorithm maps signal strength to continuous location makes it possible to skip rooms during calibration, yet still evaluate the location in those rooms.

Abstract: Method and system for measuring a relative position and orientation of range cameras using a movement of an object within a scene. In general, the method and system determine the relative pose between two cameras by measuring a path the movement of the object makes within a scene and calculating transformation parameters based on these measurements. These transformation parameters are used to determine the relative position of each camera with respect to a base camera. The system and method include other novel features, such as a data synchronization feature that uses a time offset between cameras to obtain the transformation parameters, and a technique that improves the robustness and accuracy of solving for the transformation parameters, and an interpolation process that interpolates between sampled points if there is no data at a particular instant in time.

Abstract: A process for measuring the location of people and objects carrying radio frequency (RF) transmitters (TXs) that transmit messages to a plurality of RF receivers (RXs) located in a space. Each RX is in communication with a computer of a computer network and forwards data received from the TXs to the network via its associated computer, along with a value indicating the signal strength of the received TX transmission. The signal strengths attributable to the same transmission are used to form a locating signal strength vector which is then compared to exemplary vectors generated from signal strength readings gathered in a calibration procedure from a set of representative locations in the space. In comparing the locating vector to the exemplary vectors, constraints are enforced on movements between locations (e.g., cannot pass through walls) and to probabilistically enforce expectations on transitions between locations.

Abstract: Method and system for measuring a relative position and orientation of range cameras using a movement of an object within a scene. In general, the method and system determine the relative pose between two cameras by measuring a path the movement of the object makes within a scene and calculating transformation parameters based on these measurements. These transformation parameters are used to determine the relative position of each camera with respect to a base camera. The system and method include other novel features, such as a data synchronization feature that uses a time offset between cameras to obtain the transformation parameters, and a technique that improves the robustness and accuracy of solving for the transformation parameters, and an interpolation process that interpolates between sampled points if there is no data at a particular instant in time.

Abstract: Described is a system and method in a wireless (Wi-Fi) network comprising a server, clients and various mechanisms that compute lists of other clients and resources that are physically nearby. Clients report Wi-Fi access points' signal strengths to a server, which uses that data to compute the proximity of resources to one another, including an estimate the distance between resources. The data may be returned to the client as a list of resources within short range proximity, or resources within long-range proximity, with an approximate time to that resource based on previous clients' reporting. Because proximity is used rather than absolute location, only minimal setup is needed. As the number of clients and resources that use the system increases, the server knowledge also increases with respect to the number of resources that can be found and in the physical range over which other people and places can be found.

Abstract: An image background maintenance system and method for maintaining a background model of an image sequence by processing on multiple spatial scales. These multiple spatial scales include a pixel scale, a regional scale and a frame scale. The image sequence undergoes pixel processing that determines a current background model and provides an initial pixel assignment as either a background or a foreground pixel. Region processing further refines the initial pixel assignments by considering relationships between pixels and possibly reassigning pixels. Frame processing further refines the current background model by determining whether a substantial change has occurred in the actual background and, if so, providing a more accurate background model.

Abstract: Method and system for measuring a relative position and orientation of range cameras using a movement of an object within a scene. In general, the method and system determine the relative pose between two cameras by measuring a path the movement of the object makes within a scene and calculating transformation parameters based on these measurements. These transformation parameters are used to determine the relative position of each camera with respect to a base camera. The system and method include other novel features, such as a data synchronization feature that uses a time offset between cameras to obtain the transformation parameters, and a technique that improves the robustness and accuracy of solving for the transformation parameters, and an interpolation process that interpolates between sampled points if there is no data at a particular instant in time.

Abstract: Method and system for measuring a relative position and orientation of range cameras using a movement of an object within a scene. In general, the method and system determine the relative pose between two cameras by measuring a path the movement of the object makes within a scene and calculating transformation parameters based on these measurements. These transformation parameters are used to determine the relative position of each camera with respect to a base camera. The system and method include other novel features, such as a data synchronization feature that uses a time offset between cameras to obtain the transformation parameters, and a technique that improves the robustness and accuracy of solving for the transformation parameters, and an interpolation process that interpolates between sampled points if there is no data at a particular instant in time.

Abstract: An image background maintenance system and method for maintaining a background model of an image sequence by processing on multiple spatial scales. These multiple spatial scales include a pixel scale, a regional scale and a frame scale. The image sequence undergoes pixel processing that determines a current background model and provides an initial pixel assignment as either a background or a foreground pixel. Region processing further refines the initial pixel assignments by considering relationships between pixels and possibly reassigning pixels. Frame processing further refines the current background model by determining whether a substantial change has occurred in the actual background and, if so, providing a more accurate background model.

Abstract: An image background maintenance system and method for maintaining a background model of an image sequence by processing on multiple spatial scales. These multiple spatial scales include a pixel scale, a regional scale and a frame scale. The image sequence undergoes pixel processing that determines a current background model and provides an initial pixel assignment as either a background or a foreground pixel. Region processing further refines the initial pixel assignments by considering relationships between pixels and possibly reassigning pixels. Frame processing further refines the current background model by determining whether a substantial change has occurred in the actual background and, if so, providing a more accurate background model.

Abstract: A process for determining the location of entities carrying transmitters (TXs) that transmit TX ID messages to at least one receiver (RX) connected to a computer, in a network of computers. Each RX sends data messages to its associated computer which includes an identifier identifying the TX transmitting the TX ID message, the signal strength of the received TX ID message, and a RX identifier. Each RX computer generates badge hit messages from each data message, and provides them to a centralized computer of the network. The centralized computer generates a badge hit table having a separate entry for each badge hit message, which has fields including the information received in the badge hit message and a hit time indicating the time the entry was added to the table. The badge hit table data is used to determining the location of the TXs, and so the entities.

Abstract: A process for determining the location of entities carrying transmitters (TXs) that transmit TX ID messages to at least one receiver (RX) connected to a computer, in a network of computers. Each RX sends data messages to its associated computer which includes an identifier identifying the TX transmitting the TX ID message, the signal strength of the received TX ID message, and a RX identifier. Each RX computer generates badge hit messages from each data message, and provides them to a centralized computer of the network. The centralized computer generates a badge hit table having a separate entry for each badge hit message, which has fields including the information received in the badge hit message and a hit time indicating the time the entry was added to the table. The badge hit table data is used to determining the location of the TXs, and so the entities.

Abstract: A location system for locating and determining the motion and velocity of a wireless device. The methods include direct inferences about whether a device is in motion versus static based on a statistical analysis of the variation of radio signal strengths over time. The system is trained according to a sparse set of identified locations from which signal strengths are measured. The system uses the signal properties of the identified locations to interpolate for a new location of the wireless device. The system uses a probabilistic graph where the identified locations of the floor plan, expected walking speeds of pedestrians, and independent inference of whether or not the device is in motion are used to determine the new location of the device.

Abstract: A location system for locating and determining the motion and velocity of a wireless device. The methods include direct inferences about whether a device is in motion versus static based on a statistical analysis of the variation of radio signal strengths over time. The system is trained according to a sparse set of identified locations from which signal strengths are measured. The system uses the signal properties of the identified locations to interpolate for a new location of the wireless device. The system uses a probabilistic graph where the identified locations of the floor plan, expected walking speeds of pedestrians, and independent inference of whether or not the device is in motion are used to determine the new location of the device.

Abstract: A location system for locating and determining the motion and velocity of a wireless device. The methods include direct inferences about whether a device is in motion versus static based on a statistical analysis of the variation of radio signal strengths over time. The system is trained according to a sparse set of identified locations from which signal strengths are measured. The system uses the signal properties of the identified locations to interpolate for a new location of the wireless device. The system uses a probabilistic graph where the identified locations of the floor plan, expected walking speeds of pedestrians, and independent inference of whether or not the device is in motion are used to determine the new location of the device.