Abstract: A non-transitory, processor-readable medium stores instructions that, when executed by a processor, cause the processor to generate, using a first compute device, a video file. The non-transitory, processor-readable medium also stores instructions that, when executed by a processor, cause the processor to cause the video file to be sent to a second compute device that is cloud based, to cause the second compute device to: encode the video file, using a set of at least one software container, to generate an encoded video file; execute, at the set of at least one software container, a streaming protocol to generate a stream based on the encoded video file; and cause, via the set of at least one software container, generation of a set of analytics associated with the video file, based on the stream and using a virtualized software application environment.

Abstract: A non-transitory, processor-readable medium stores instructions that, when executed by a processor, cause the processor to generate, using a first compute device, a video file. The non-transitory, processor-readable medium also stores instructions that, when executed by a processor, cause the processor to cause the video file to be sent to a second compute device that is cloud based, to cause the second compute device to: encode the video file, using a set of at least one software container, to generate an encoded video file; execute, at the set of at least one software container, a streaming protocol to generate a stream based on the encoded video file; and cause, via the set of at least one software container, generation of a set of analytics associated with the video file, based on the stream and using a virtualized software application environment.

Abstract: A trajectory-based object search process includes receiving a user request specifying a geographic region of interest and/or a time period of interest. A set of video-derived object trajectories is identified based on the user request. At least one event is identified based on the set of video-derived object trajectories, by processing each video-derived object trajectory individually or by aggregating video-derived object trajectories, from the set of video-derived object trajectories, that overlap with respect to at least one feature. For each event, a preview image is selected that includes a thumbnail image and/or a video frame, based on the user request and using a ranking algorithm, and event metadata associated with the preview image is received. Also for each event, a video segment associated with that event is received, and the preview image and/or the video segment is caused to be displayed to a user associated with the user request.

Abstract: A system is provided that learns a radar scene's background and that filters radar tracks determined to be in the radar scene background; The system including processing circuitry configured with executable instructions to accesses radar tracks that include radar measurements; to use the measurements to determine a persistent radar object in a radar scene background; and to subsequently filter accessed radar tracks having locations within the radar scene background.

Abstract: An imaging system is provided comprising: a memory storing instructions which, when executed by processing circuitry, cause the processing circuitry to perform operations comprising: determining multiple image regions of interest (ROIs) within a camera image plane that correspond to one or more three-dimensional (3D) world object images; determining multiple radar ROIs that correspond to one or more 3D world objects; determining 3D world distances corresponding to the radar ROIs; determining multiple co-registered ROI pairs by co-registering individual image ROIs with individual radar ROIs corresponding to common 3D world objects; adjusting one or more parameters associated with the camera, based upon the co-registered ROI pairs.

Abstract: A trajectory-based object search process includes receiving a user request specifying a geographic region of interest and/or a time period of interest. A set of video-derived object trajectories is identified based on the user request. At least one event is identified based on the set of video-derived object trajectories, by processing each video-derived object trajectory individually or by aggregating video-derived object trajectories, from the set of video-derived object trajectories, that overlap with respect to at least one feature. For each event, a preview image is selected that includes a thumbnail image and/or a video frame, based on the user request and using a ranking algorithm, and event metadata associated with the preview image is received. Also for each event, a video segment associated with that event is received, and the preview image and/or the video segment is caused to be displayed to a user associated with the user request.

Abstract: A non-transitory, processor-readable medium stores instructions that, when executed by a processor, cause the processor to generate, using a first compute device, a video file. The non-transitory, processor-readable medium also stores instructions that, when executed by a processor, cause the processor to cause the video file to be sent to a second compute device that is cloud based, to cause the second compute device to: encode the video file, using a set of at least one software container, to generate an encoded video file; execute, at the set of at least one software container, a streaming protocol to generate a stream based on the encoded video file; and cause, via the set of at least one software container, generation of a set of analytics associated with the video file, based on the stream and using a virtualized software application environment.

Abstract: A trajectory-based object search process includes receiving a user request specifying a geographic region of interest and/or a time period of interest. A set of video-derived object trajectories is identified based on the user request. At least one event is identified based on the set of video-derived object trajectories, by processing each video-derived object trajectory individually or by aggregating video-derived object trajectories, from the set of video-derived object trajectories, that overlap with respect to at least one feature. For each event, a preview image is selected that includes a thumbnail image and/or a video frame, based on the user request and using a ranking algorithm, and event metadata associated with the preview image is received. Also for each event, a video segment associated with that event is received, and the preview image and/or the video segment is caused to be displayed to a user associated with the user request.

Abstract: A method for performing detection-based object searches includes receiving a user request indicating a region of interest, a timeframe of interest, or an object of interest. A signal is sent to cause execution of a query to identify object detections based on the user request. A signal representing at least one event identified in response to the query is received. For each event from the at least one event, a thumbnail image is identified based on the user request and using a ranking algorithm. A video frame identified based on the thumbnail image is received, and a video segment associated with the video frame is retrieved, A preview image clip that includes the video frame and the video segment is generated and displayed to a user associated with the user request.

Abstract: A non-transitory, processor-readable medium stores instructions that, when executed by a processor, cause the processor to generate, using a first compute device, a video file. The non-transitory, processor-readable medium also stores instructions that, when executed by a processor, cause the processor to cause the video file to be sent to a second compute device that is cloud based, to cause the second compute device to: encode the video file, using a set of at least one software container, to generate an encoded video file; execute, at the set of at least one software container, a streaming protocol to generate a stream based on the encoded video file; and cause, via the set of at least one software container, generation of a set of analytics associated with the video file, based on the stream and using a virtualized software application environment.

Abstract: An imaging system is provided comprising: a memory storing instructions which, when executed by processing circuitry, cause the processing circuitry to perform operations comprising: determining multiple image regions of interest (ROIs) within a camera image plane that correspond to one or more three-dimensional (3D) world object images; determining multiple radar ROIs that correspond to one or more 3D world objects; determining 3D world distances corresponding to the radar ROIs; determining multiple co-registered ROI pairs by co-registering individual image ROIs with individual radar ROIs corresponding to common 3D world objects; adjusting one or more parameters associated with the camera, based upon the co-registered ROI pairs.

Abstract: An imaging system is provided comprising: a memory storing instructions which, when executed by processing circuitry, cause the processing circuitry to perform operations comprising: determining multiple image regions of interest (ROIs) within a camera image plane that correspond to one or more three-dimensional (3D) world object images; determining multiple radar ROIs that correspond to one or more 3D world objects; determining 3D world distances corresponding to the radar ROIs; determining multiple co-registered ROI pairs by co-registering individual image ROIs with individual radar ROIs corresponding to common 3D world objects; adjusting one or more parameters associated with the camera, based upon the co-registered ROI pairs.

Abstract: A system is provided that learns a radar scene's background and that filters radar tracks determined to be in the radar scene background; The system including processing circuitry configured with executable instructions to accesses radar tracks that include radar measurements; to use the measurements to determine a persistent radar object in a radar scene background; and to subsequently filter accessed radar tracks having locations within the radar scene background.

Abstract: An imaging system is provided comprising: a memory storing instructions which, when executed by processing circuitry, cause the processing circuitry to perform operations comprising: determining multiple image regions of interest (ROIs) within a camera image plane that correspond to one or more three-dimensional (3D) world object images; determining multiple radar ROIs that correspond to one or more 3D world objects; determining 3D world distances corresponding to the radar ROIs; determining multiple co-registered ROI pairs by co-registering individual image ROIs with individual radar ROIs corresponding to common 3D world objects; adjusting one or more parameters associated with the camera, based upon the co-registered ROI pairs.

Abstract: An electronic device may generate content that is to be displayed on a display. The display may have an array of liquid crystal display pixels for displaying image frames of the content. The image frames may be displayed with positive and negative polarities to help reduce charge accumulation effects. A charge accumulation tracker may analyze the image frames to determine when there is a risk of excess charge accumulation. The charge accumulation tracker may analyze information on gray levels, frame duration, and frame polarity. The charge accumulation tracker may compute a charge accumulation metric for entire image frames or may process subregions of each frame separately. When subregions are processed separately, each subregion may be individually monitored for a risk of excess charge accumulation.

Abstract: An electronic device may generate content that is to be displayed on a display. The display may have an array of liquid crystal display pixels for displaying image frames of the content. The image frames may be displayed with positive and negative polarities to help reduce charge accumulation effects. A charge accumulation tracker may analyze the image frames to determine when there is a risk of excess charge accumulation. The charge accumulation tracker may analyze information on gray levels, frame duration, and frame polarity. The charge accumulation tracker may compute a charge accumulation metric for entire image frames or may process subregions of each frame separately. When subregions are processed separately, each subregion may be individually monitored for a risk of excess charge accumulation.

Abstract: A thermoacoustic imaging device is provided having a transmitter configured to provide an electromagnetic transmit signal (e.g. a continuous sinusoidal signal) to an object being imaged. The transmit signal is a modulated continuous-wave signal based on a carrier frequency signal fc modulated at a modulation frequency at or near fm. The detector is further configured to receive an acoustic signal from the object being imaged, and is responsive to acoustic frequencies at or near 2fm. A non-linear thermoacoustic effect in the object being imaged generates the acoustic signal from the object being imaged. Spectroscopic maps could be generated and imaged object could be analyzed. The device enhances signal-to-noise ratio of the reconstructed image and reduces the requirement of peak power in thermoacoustic imaging systems. In addition, the generated pressure of the imaged object is separated from microwave leakage and feedthrough in frequency through the nonlinear thermoacoustic effect.

Abstract: An electronic device may generate content that is to be displayed on a display. The display may have an array of liquid crystal display pixels for displaying image frames of the content. The image frames may be displayed with positive and negative polarities to help reduce charge accumulation effects. A charge accumulation tracker may analyze the image frames to determine when there is a risk of excess charge accumulation. The charge accumulation tracker may analyze information on gray levels, frame duration, and frame polarity. The charge accumulation tracker may compute a charge accumulation metric for entire image frames or may process subregions of each frame separately. When subregions are processed separately, each subregion may be individually monitored for a risk of excess charge accumulation.

Abstract: Systems and methods for labeling radar tracks for machine learning are disclosed. According to some aspects, a machine accesses data from radar unit(s), the data from the radar unit(s) comprising radar tracks, each radar track comprising one or more of the following: Doppler and micro-Doppler measurement(s), range measurement(s), and angle measurement(s). The machine accesses data from computer vision device(s), the data from the computer vision device(s) comprising image(s), the data from the computer vision device(s) being associated with a common geographic region and a common time period with the data from the radar unit(s). The machine labels, using an image recognition module, objects in the image(s). The machine determines, based on the common geographic region and the common time period, that labeled object(s) in the image(s) map to radar track(s). The machine labels the radar track(s) based on labels of the labeled objects.

Abstract: An electronic device may generate content that is to be displayed on a display. The display may have an array of liquid crystal display pixels for displaying image frames of the content. The image frames may be displayed with positive and negative polarities to help reduce charge accumulation effects. A charge accumulation tracker may analyze the image frames to determine when there is a risk of excess charge accumulation. The charge accumulation tracker may analyze information on gray levels, frame duration, and frame polarity. The charge accumulation tracker may compute a charge accumulation metric for entire image frames or may process subregions of each frame separately. When subregions are processed separately, each subregion may be individually monitored for a risk of excess charge accumulation.