Abstract: A media items to be shared with users of a content sharing service are identified. Each of the media items corresponds to a video recording generated by a client device that depicts one or more objects corresponding to a real-world event and/or a geographic location. A location of the client device that generated the video recording corresponding to a respective media item of the media items is determined based on image features depicted in a set of frames of the video recording. A request for content associated with at least one of the real-world event and/or the geographic location is received from another client device connected to the content sharing service. The media items and, for each of the media items, an indication of the location of the client device that generated the corresponding video recording are provided in accordance with the request for content.

Abstract: A set of media items to be shared with users of a content sharing service is identified. Each of the set of media items corresponds to a video recording generated by a client device that depicts one or more objects corresponding to a real-world event at a geographic location. A positioning of the client device that generated the video recording corresponding to a respective media item of the set of media items is determined. The positioning is determined based on image features depicted in a set of frames of the video recording. A request for content associated with at least one of the real-world event or the geographic location is received from another client device connected to the content sharing service. The set of media items and, for each of the set of media items, an indication of the determined positioning of the client device that generated the corresponding video recording is provided in accordance with the request for content.

Abstract: A set of media items to be shared with users of a content sharing service is identified. Each of the set of media items corresponds to a video recording generated by a client device that depicts one or more objects corresponding to a real-world event at a geographic location. A positioning of the client device that generated the video recording corresponding to a respective media item of the set of media items is determined. The positioning is determined based on image features depicted in a set of frames of the video recording. A request for content associated with at least one of the real-world event or the geographic location is received from another client device connected to the content sharing service. The set of media items and, for each of the set of media items, an indication of the determined positioning of the client device that generated the corresponding video recording is provided in accordance with the request for content.

Abstract: The technology disclosed herein includes a method for determining the position of multiple cameras relative to each other. In one example, the method may include: receiving, by a processor, a first video recording of a first camera and a second video recording of a second camera; selecting a set of frames of the first video recording; determining a blurriness measure for multiple frames of the set; identifying feature points in multiple frames of the set; selecting a frame from the set of frames based on the blurriness measure and the identified feature points; and determining a position of a first camera relative to a second camera by comparing the selected frame with a frame of the second video recording.

Abstract: A method of analyzing breathing data representing a shape of the trunk of a subject 104 as a function of time to monitor and/or analyze the subject's breathing pattern. The data is measured and processed into a data array relating to a 2-dimensional grid having grid points, a position in space of the shape at each grid point and points of time. The method includes the steps of mapping the data array onto a 2-dimensional array, decomposing the 2-dimensional array and forming a signature of the subject 104 from the decomposed 2-dimensional array representing a motion pattern.

Abstract: The technology disclosed herein includes a method for determining the position of multiple cameras relative to each other. In one example, the method may include: receiving, by a processor, a first video recording of a first camera and a second video recording of a second camera; selecting a set of frames of the first video recording; determining a blurriness measure for multiple frames of the set; identifying feature points in multiple frames of the set; selecting a frame from the set of frames based on the blurriness measure and the identified feature points; and determining a position of a first camera relative to a second camera by comparing the selected frame with a frame of the second video recording.

Abstract: A method of analysing breathing data representing a shape of the trunk of a subject 104 as a function of time to monitor and/or analyse the subject's breathing pattern. The data is measured and processed into a data array relating to a 2-dimensional grid having grid points, a position in space of the shape at each grid point and points of time. The method includes the steps of mapping the data array onto a 2-dimensional array, decomposing the 2-dimensional array and forming a signature of the subject 104 from the decomposed 2-dimensional array representing a motion pattern.

Abstract: A method of analyzing breathing data representing a shape of the trunk of a subject 104 as a function of time to monitor and/or analyze the subject's breathing pattern. The data is measured and processed into a data array relating to a 2-dimensional grid having grid points, a position in space of the shape at each grid point and points of time. The method includes the steps of mapping the data array onto a 2-dimensional array, decomposing the 2-dimensional array and forming a signature of the subject 104 from the decomposed 2-dimensional array representing a motion pattern.

Abstract: A method for determining the position of multiple cameras relative to each other includes at a processor, receiving video data from at least one video recording taken by each camera; selecting a subset of frames of each video recording, including determining relative blurriness of each frame of each video recording, selecting frames having a lowest relative blurriness, counting features points in each of the lowest relative blurriness frames, and selecting for further analysis, lowest relative blurriness frames having a highest count of feature points; and processing each selected subset of frames from each video recording to estimate the location and orientation of each camera.

Abstract: A method and system of monitoring an object (e.g., for change in configuration of a person) includes projecting a radiation pattern onto the object; recording at a first time first image data representing a portion of the projected radiation pattern on the object, the first image data representative of a three dimensional configuration of the object at the first time; recording at a second time second image data representing a portion of the projected pattern of radiation on the object, the second image data representative of a three dimensional configuration of the object at the second time; and processing the first and second image data to generate differential data representative of a change in the configuration of the object between the first and second times.

Abstract: A method and system of monitoring an object (e.g., for change in configuration of a person) includes projecting a radiation pattern onto the object; recording at a first time first image data representing a portion of the projected radiation pattern on the object, the first image data representative of a three dimensional configuration of the object at the first time; recording at a second time second image data representing a portion of the projected pattern of radiation on the object, the second image data representative of a three dimensional configuration of the object at the second time; and processing the first and second image data to generate differential data representative of a change in the configuration of the object between the first and second times.

Abstract: A method of analysing breathing data representing a shape of the trunk of a subject 104 as a function of time to monitor and/or analyse the subject's breathing pattern. The data is measured and processed into a data array relating to a 2-dimensional grid having grid points, a position in space of the shape at each grid point and points of time. The method includes the steps of mapping the data array onto a 2-dimensional array, decomposing the 2-dimensional array and forming a signature of the subject 104 from the decomposed 2-dimensional array representing a motion pattern.

Abstract: A method and system of monitoring an object (e.g., for change in configuration of a person) includes projecting a radiation pattern onto the object; recording at a first time first image data representing a portion of the projected radiation pattern on the object, the first image data representative of a three dimensional configuration of the object at the first time; recording at a second time second image data representing a portion of the projected pattern of radiation on the object, the second image data representative of a three dimensional configuration of the object at the second time; and processing the first and second image data to generate differential data representative of a change in the configuration of the object between the first and second times.

Abstract: A method and system of monitoring an object (e.g., for change in configuration of a person) includes projecting a radiation pattern onto the object; recording at a first time first image data representing a portion of the projected radiation pattern on the object, the first image data representative of a three dimensional configuration of the object at the first time; recording at a second time second image data representing a portion of the projected pattern of radiation on the object, the second image data representative of a three dimensional configuration of the object at the second time; and processing the first and second image data to generate differential data representative of a change in the configuration of the object between the first and second times.

Abstract: A flame detection apparatus and method includes a camera, preferably operating in the near I.R. which produces a succession of images of a space to be monitored. The image intensity of each pixel in each image is converted to a binary value by comparing it with the average intensity value for that image. For each pixel in an image the average intensity value for all of the images is calculated. The binary intensity value of each pixel in an image is then compared with the binary intensity value of the corresponding pixels in all the other images to produce a crossing frequency value dependent on the number of times those binary values change state. The average intensity values and the crossing frequency values are then processed for each pixel according to a predetermined relationship to produce a constant. If the values of this constant for a cluster of adjacent pixels are found to be the same or nearly so, this is considered to indicate a flame.