Abstract: In one aspect, an example method includes (i) obtaining video that depicts an area across multiple frames of the video, wherein the area is part of a scene of the video, and wherein the area is suitable for having an object inserted therein; (ii) detecting the area within the obtained video and determining area characteristic data associated with the detected area; (iii) determining scene attribute data associated with the scene; (iv) using at least the determined area characteristic data and the determined scene attribute data as a basis to select an object from among a set of multiple candidate objects; (v) inserting into the detected area the selected object to generate video that is a modified version of the obtained video; and (vi) outputting for presentation the generated video.

Abstract: Disclosed herein are system, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for reducing and/or eliminating false positive alarm triggers. Detector devices positioned throughout an environment scan for known events that are likely indicative of an alarm condition. A source device that may generate such a sound or image may imprint a fingerprint on to the event that can be detectable by the detector devices but is imperceptible to humans. Additionally, the detector devices may use directionality and known locations of source devices to determine if a triggering event occurred at a known location of a source device. An alarm suppression decision may occur at the detector device and/or relevant information may be sent from the various detectors to a central console for a final alarm decision.

Abstract: Disclosed herein are system, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof for providing a monitoring and alerting service for a premises comprising a set of Internet of Things (IoT) devices. An example embodiment operates by analyzing one or more of user input provided to the monitoring and alerting service or sensor data collected from at least the set of IoT devices, defining, based at least on the analyzing, an event whose occurrence can be monitored for using at least one or more IoT devices in the set of IoT devices, monitoring for an occurrence of the event using at least the one or more devices in the set of IoT devices, detecting the occurrence of the event based on the monitoring and, in response to detecting the occurrence of the event, generating an alert.

Abstract: A method and system for use of context information to disambiguate an automation-configuration command. In an example method, a computing system receives a voice command uttered by a user into a voice-interface device, the voice command describing an Internet-of-Things (IoT) automation. Further, in response to receiving the voice command, the computing system determines, based on context information not specified by the voice command, which of multiple IoT devices should be a subject of an IoT rule that implements the described IoT automation, and provisions the IoT rule with the determined IoT device as the subject of the IoT rule. In example implementations, the context information could be based on network signaling between devices, ambient audio in the user's environment, and/or one or more other factors.

Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for sharing video streams in a camera system network. The video streams may be modified and/or masked to obscure private video stream features from being shared. An example embodiment operates by linking a first camera system to a first user device. The first camera system detects a second camera system in its field of view, wherein the second camera system is linked to a second user device. Upon exchanging requests to share video streams, the first and second user devices may view the video streams from both camera systems. The video streams may be modified to mask and/or obscure private property and/or known persons to preserve privacy despite sharing video streams. For example, the first camera system may modify and stream a masked video stream to the second user device.

Abstract: In one aspect, an example method includes (i) obtaining, by a computing system, video data representing video content; (ii) analyzing, by the computing system, the video data to identify an event that is a subject of the video content; (iii) using, by the computing system, the identified event as a basis to select audio content; and (iv) performing, by the computing system, an operation that facilitates editing the video content to include the selected audio content.

Abstract: A RADAR system and associated methods are used to detect obstacles obscured from view when backing a trailer. An autonomous tractor is equipped with a rear facing RADAR device that has a field-of-view under the trailer and is configured to output RADAR returns from reflections. A controller of the tractor classifies RADAR returns from the RADAR device according to a number of reflections by a dock wall and a trailer face (e.g., a back end of the trailer) of a corresponding RADAR beam. The RADAR returns are correlated based on distance, and distance of a RADAR return from an obstacle is corrected based on the number of reflections. Advantageously, by processing RADAR returns from both direct and reflected RADAR beams, the controller is able to detect obstacles hidden behind the trailer and flag the obstacles as a hazard.

Abstract: In one aspect, an example method includes causing a content-presentation device to output reference visual content and causing a lighting device to emit light in accordance with a lighting parameter. The method can also include using a camera to continually capture an environment that includes the reference visual content and the emitted light and while continually capturing the environment, analyzing the generated capture data to compare the light emitted in accordance with the lighting parameter with the reference visual content, and continually cause the lighting device to adjust the lighting parameter until detecting, based on the comparing, that the adjusted emitted light corresponds to the reference visual content. The method can further include calibrating the lighting device at least by causing storage of the adjusted lighting parameter and by causing the lighting device to be configured to emit light in accordance with the stored lighting parameter.

Abstract: In one aspect, an example method includes: (i) a computing system obtaining media content; (ii) the computing system extracting from the obtained media content, audio content; (iii) the computing system using at least the extracted audio content to obtain sentiment data associated with the audio content; (iv) the computing system using the obtained sentiment data as a basis to modify a video content component of the media content, thereby generating a modified version of the media content; and (v) the computing system outputting for presentation the generated modified media content.

Abstract: In one aspect, an example method includes (i) receiving, from a content-distribution system, video comprising a watermark; (ii) extracting the watermark from the video; (iii) based on the extracted watermark, determining a content-creation attribute of the video that indicates a process by which the video was created, wherein the determining comprises using the watermark to select the content-creation attribute from among a set of two or more content-creation attributes comprising organically-generated video and synthetically-generated video; and (iv) in response to determining the content-creation attribute of the video, causing a content-presentation device to perform an action.

Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for cue point discovery for content. For example, system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof are provided for using unsupervised machine learning to automatically classify cue points for episodic content. The cue points can be associates with an opening credits section, an end credits section, a recap section, or a behind-the-scenes section.

Abstract: In one aspect, a method includes receiving video content comprising a first data portion comprising parameters that control a visual appearance of frames of video content presented by a content-presentation device. The content-presentation device is communicatively coupled to a light unit that is (i) present in a viewing area of the content-presentation device and (ii) configured to provide ambient light in the viewing area. The method also includes extracting, from the received video content, a second data portion, separate from the first data portion, specifying one or more light control parameters that a controller associated with the light unit is configured to interpret as instructions for controlling the light unit. The method also includes transmitting the extracted second data portion to the controller to facilitate the controller controlling the light unit according to the specified one or more light control parameters.

Abstract: In one aspect, disclosed is an example method for use in connection with a media-presentation device having an associated presentation area, the method including: (i) obtaining presentation area data associated with the presentation area; (ii) determining that the obtained presentation area data satisfies each and every condition of a condition set; (iii) responsive to at least determining that the obtained presentation area data satisfies each and every condition of the condition set, identifying an upcoming media segment insertion point within a media program; and (iv) facilitating the media-presentation device outputting for presentation a media segment starting at the identified media segment insertion point within the media program.

Abstract: In one aspect, disclosed is an example method for use by a lighting device including a microphone and a light source, the method including: (i) receiving, by the lighting device via the microphone, an audio signal; (ii) decoding and extracting, by the lighting device, a lighting device control instruction from the received audio signal; and (iii) using, by the lighting device, at least the decoded and extracted lighting device control instruction as a basis to control operation of the light source.

Abstract: A method and a system for using crowdsourcing as a basis to predict and respond to emergency impact. An example method includes (i) a computing system receiving emergency-state reporting provided by multiple customer premises in a region, (ii) the computing system determining, based on the received emergency-state reporting provided by the multiple customer premises in the region, that a region-wide emergency situation exists in the region, and (iii) the computing system taking action, in response to the determining, based on the emergency-state reporting provided by the multiple customer premises in the region, that the region-wide emergency situation exists in the region.

Abstract: In one aspect, disclosed is an example method for use in connection with a media-presentation device presenting a media program via a display screen of the media-presentation device, the method including: (i) during presentation of a temporal portion of the media program, identifying an audience engagement region of presented content, wherein the identified audience engagement region is less than an entirety of a display area that corresponds to the display screen; (ii) using at least the identified audience engagement region as a basis to select a media segment from among multiple candidate media segments; (iii) identifying an upcoming media segment insertion point within the media program; and (iv) facilitating the media-presentation device inserting, at the identified media segment insertion point within the media program, the selected media segment.

Abstract: A method and system for use of context information to disambiguate an automation-configuration command. In an example method, a computing system receives a voice command uttered by a user into a voice-interface device, the voice command describing an Internet-of-Things (IoT) automation. Further, in response to receiving the voice command, the computing system determines, based on context information not specified by the voice command, which of multiple IoT devices should be a subject of an IoT rule that implements the described IoT automation, and provisions the IoT rule with the determined IoT device as the subject of the IoT rule. In example implementations, the context information could be based on network signaling between devices, ambient audio in the user's environment, and/or one or more other factors.

Abstract: In one aspect, disclosed is an example method for use in connection with a media-presentation device presenting a media program via a display screen of the media-presentation device, the method including: (i) during presentation of a temporal portion of the media program, identifying an audience engagement region of presented content, wherein the identified audience engagement region is less than an entirety of a display area that corresponds to the display screen; (ii) using at least the identified audience engagement region as a basis to select a media segment from among multiple candidate media segments; (iii) identifying an upcoming media segment insertion point within the media program; and (iv) facilitating the media-presentation device inserting, at the identified media segment insertion point within the media program, the selected media segment.

Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for cue point discovery for content. For example, system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof are provided for using unsupervised machine learning to automatically classify cue points for episodic content. The cue points can be associates with an opening credits section, an end credits section, a recap section, or a behind-the-scenes section.

Abstract: In one aspect, disclosed is an example method for use in connection with a media-presentation device having an associated presentation area, the method including: (i) obtaining presentation area data associated with the presentation area; (ii) determining that the obtained presentation area data satisfies each and every condition of a condition set; (iii) responsive to at least determining that the obtained presentation area data satisfies each and every condition of the condition set, identifying an upcoming media segment insertion point within a media program; and (iv) facilitating the media-presentation device outputting for presentation a media segment starting at the identified media segment insertion point within the media program.