Abstract: Systems and methods may be directed to de-blurring panoramic images and/or video. An image processor may receive a frame, where the frame comprises a plurality of pixel values arranged in a grid. The image processor may divide the frame into a first section and a second section. The image processor may determine a first motion kernel for the first section and apply the first motion kernel to the first section. The image processor may also determine a second motion kernel for the second section and apply the second motion kernel to the second section.

Abstract: A video capture device may include multiple cameras that simultaneously capture video data. The video capture device and/or one or more remote computing resources may stitch the video data captured by the multiple cameras to generate stitched video data that corresponds to 360° video. The remote computing resources may apply one or more algorithms to the stitched video data to adjust the color characteristics of the stitched video data, such as lighting, exposure, white balance contrast, and saturation. The remote computing resources may further smooth the transition between the video data captured by the multiple cameras to reduce artifacts such as abrupt changes in color as a result of the individual cameras of the video capture device having different video capture settings. The video capture device and/or the remote computing resources may generate a panoramic video that may include up to a 360° field of view.

Abstract: Various embodiments enable a primary user to be identified and tracked using stereo association and multiple tracking algorithms. For example, a face detection algorithm can be run on each image captured by a respective camera independently. Stereo association can be performed to match faces between cameras. If the faces are matched and a primary user is determined, a face pair is created and used as the first data point in memory for initializing object tracking. Further, features of a user's face can be extracted and the change in position of these features between images can determine what tracking method will be used for that particular frame.

Abstract: Devices, systems and methods are disclosed for identifying content in video data and creating content-based zooming and panning effects to emphasize the content. Contents may be detected and analyzed in the video data using computer vision, machine learning algorithms or specified through a user interface. Panning and zooming controls may be associated with the contents, panning or zooming based on a location and size of content within the video data. The device may determine a number of pixels associated with content and may frame the content to be a certain percentage of the edited video data, such as a close-up shot where a subject is displayed as 50% of the viewing frame. The device may identify an event of interest, may determine multiple frames associated with the event of interest and may pan and zoom between the multiple frames based on a size/location of the content within the multiple frames.

Abstract: Various embodiments enable a primary user to be identified and tracked using stereo association and multiple tracking algorithms. For example, a face detection algorithm can be run on each image captured by a respective camera independently. Stereo association can be performed to match faces between cameras. If the faces are matched and a primary user is determined, a face pair is created and used as the first data point in memory for initializing object tracking. Further, features of a user's face can be extracted and the change in position of these features between images can determine what tracking method will be used for that particular frame.

Abstract: Devices, systems and methods are disclosed for identifying content in video data and creating content-based zooming and panning effects to emphasize the content. Contents may be detected and analyzed in the video data using computer vision, machine learning algorithms or specified through a user interface. Panning and zooming controls may be associated with the contents, panning or zooming based on a location and size of content within the video data. The device may determine a number of pixels associated with content and may frame the content to be a certain percentage of the edited video data, such as a close-up shot where a subject is displayed as 50% of the viewing frame. The device may identify an event of interest, may determine multiple frames associated with the event of interest and may pan and zoom between the multiple frames based on a size/location of the content within the multiple frames.

Abstract: A radio frequency (RF) processing circuit used in a wireless communication device for processing a plurality of wireless signals is disclosed. The RF processing circuit comprises an RF front-end circuit and a control unit. The RF front-end circuit is coupled to a plurality of antennas and a plurality of communication modules and is used for switching connections between the plurality of antennas and the plurality of communication modules according to a control signal. The control unit is coupled to the RF front-end circuit and is used for generating the control signal according to a frequency band and operation conditions of each communication module. The RF front-end circuit further comprises a switch module and a frequency multiplexing module.

Abstract: Automated person re-identification may be assisted by consideration of attributes of the person in a joint classification with matching of the person. By both solving for similarities in a plurality of attributes and identities, discriminative interactions may be captured. Automated person re-identification may be assisted by consideration of a semantic color name. Rather than a color histogram, probability distributions are mapped to color terms of the semantic color name. Using other descriptors as well, similarity measures for the various descriptors are weighted and combined into a score. Either or both considerations may be used.

Abstract: Various embodiments enable a primary user to be identified and tracked using stereo association and multiple tracking algorithms. For example, a face detection algorithm can be run on each image captured by a respective camera independently. Stereo association can be performed to match faces between cameras. If the faces are matched and a primary user is determined, a face pair is created and used as the first data point in memory for initializing object tracking. Further, features of a user's face can be extracted and the change in position of these features between images can determine what tracking method will be used for that particular frame.

Abstract: A forensic video search user interface is disclosed that accesses databases of stored video event metadata from multiple camera streams and facilitates the workflow of search of complex global events that are composed of a number of simpler, low complexity events.

Abstract: A method for tracking pedestrians in a video sequence, where each image frame of the video sequence corresponds to a time step, includes using marginal space learning to sample a prior probability distribution p(xt|Zt?1) of multi-person identity assignments given a set of feature measurements from all previous image frames, using marginal space learning to estimate an observation likelihood distribution p(zt|xt) of the set of features given a set of multi-person identity assignments sampled from the prior probability distribution, calculating a posterior probability distribution p(xt|Zt) from the observation likelihood distribution p(zt|xt) and the prior probability distribution p(xt|Zt?1), and using marginal space learning to estimate the prior probability distribution p(xt+1|Zt) for a next image frame given the posterior probability distribution p(xt|Zt) and a probability p(xt+1|xt), where the posterior probability distribution of multi-person identity assignments corresponds to a set of pedestrian detectio

Abstract: A radio frequency (RF) processing circuit used in a wireless communication device for processing a 10 plurality of wireless signals is disclosed. The RF processing circuit comprises an RF front-end circuit, coupled to a plurality of antennas and a plurality of communication modules for switching connections between the plurality of antennas and the plurality of communication modules according to a control signal; and a control unit, coupled to the RF front-end circuit for generating the control signal according to a frequency band and operation conditions of each communication module; wherein the control unit controls the RF front-end circuit to connect each communication module and one of the plurality of antennas, and the wireless communication modules which are connected to a same antenna correspond to different frequency bands.

Abstract: In an embodiment of the disclosure, an electronic device arranged for eliminating wireless noise interference is provided. The electronic device includes a circuit board and two first metal components. The metal components are arranged on different sides of the circuit board. Each of the first metal components comprises a first terminal and a second terminal opposite to the first terminal. The first terminal is coupled to the circuit board and the second terminal is open loop. The length of the first metal component is about one-fourth wavelength of a pre-determined frequency.

Abstract: In an embodiment of the disclosure, an electronic device arranged for eliminating wireless noise interference is provided. The electronic device includes a circuit board and two first metal components. The metal components are arranged on different sides of the circuit board. Each of the first metal components comprises a first terminal and a second terminal opposite to the first terminal The first terminal is coupled to the circuit board and the second terminal is open loop. The length of the first metal component is about one-fourth wavelength of a pre-determined frequency.

Abstract: The present invention discloses an antenna for a wireless communication device, including a radiator including a first fixing segment, and a first connecting unit including a first fixture unit and a second fixture unit for holding the first fixing segment such that the radiator is electrically connect to a circuit.

Abstract: The present invention discloses a high gain antenna. The high gain antenna includes a first dipole antenna, formed on a substrate; a parallel reflection metal sheet, formed on the substrate and in parallel with the first dipole antenna; a first vertical reflection metal sheet, vertically disposed on a front side of the substrate and behind the first dipole antenna; and a second vertical reflection metal sheet, vertically disposed on a back side of the substrate and behind the first dipole antenna.

Abstract: Automated person re-identification may be assisted by consideration of attributes of the person in a joint classification with matching of the person. By both solving for similarities in a plurality of attributes and identities, discriminative interactions may be captured. Automated person re-identification may be assisted by consideration of a semantic color name. Rather than a color histogram, probability distributions are mapped to color terms of the semantic color name. Using other descriptors as well, similarity measures for the various descriptors are weighted and combined into a score. Either or both considerations may be used.

Abstract: The present invention discloses a high gain antenna. The high gain antenna includes a first dipole antenna, formed on a substrate; a parallel reflection metal sheet, formed on the substrate and in parallel with the first dipole antenna; a first vertical reflection metal sheet, vertically disposed on a front side of the substrate and behind the first dipole antenna; and a second vertical reflection metal sheet, vertically disposed on a back side of the substrate and behind the first dipole antenna.

Abstract: A method for tracking pedestrians in a video sequence, where each image frame of the video sequence corresponds to a time step, includes using marginal space learning to sample a prior probability distribution p(xt|Zt?1) of multi-person identity assignments given a set of feature measurements from all previous image frames, using marginal space learning to estimate an observation likelihood distribution p(zt|xt) of the set of features given a set of multi-person identity assignments sampled from the prior probability distribution, calculating a posterior probability distribution p(xt|Zt) from the observation likelihood distribution p(zt|xt) and the prior probability distribution p(xt|Zt?1), and using marginal space learning to estimate the prior probability distribution p(xt+1|Zt) for a next image frame given the posterior probability distribution p(xt|Zt) and a probability p(xt+1|xt), where the posterior probability distribution of multi-person identity assignments corresponds to a set of pedestrian detectio