Embodiments include a system, method, and computer program product that enable secure access to cameras in smart buildings. Some embodiments control outbound video from an environment such as a local network through an intelligent on-event video pushing mechanism. The local intelligent on-event video pushing mechanism hides the IP address of a source video camera, transcodes the video to a reduced size for wide area distribution, and pushes video to a recipient upon an event triggered received within the local environment (e.g., the local network.) Embodiments enable a remote video client on the far-side of the local network firewall to view the video streams of cameras on the near-side of the local network firewall when an event or trigger occurs.

A learning model is trained for rate-distortion behavior prediction against a corpus of a video hosting platform and used to determine optimal bitrate allocations for video data given video content complexity across the corpus of the video hosting platform. Complexity features of the video data are processed using the learning model to determine a rate-distortion cluster prediction for the video data, and transcoding parameters for transcoding the video data are selected based on that prediction. The rate-distortion clusters are modeled during the training of the learning model, such as based on rate-distortion curves of video data of the corpus of the video hosting platform and based on classifications of such video data. This approach minimizes total corpus egress and/or storage while further maintaining uniformity in the delivered quality of videos by the video hosting platform.

A learning model is trained for rate-distortion behavior prediction against a corpus of a video hosting platform and used to determine optimal bitrate allocations for video data given video content complexity across the corpus of the video hosting platform. Complexity features of the video data are processed using the learning model to determine a rate-distortion cluster prediction for the video data, and transcoding parameters for transcoding the video data are selected based on that prediction. The rate-distortion clusters are modeled during the training of the learning model, such as based on rate-distortion curves of video data of the corpus of the video hosting platform and based on classifications of such video data. This approach minimizes total corpus egress and/or storage while further maintaining uniformity in the delivered quality of videos by the video hosting platform.

Techniques for video processing, including video coding, video decoding and video transcoding are described. One example method includes performing a conversion between a video picture that includes one or more tiles and one or more rectangular slices and a bitstream of the video according to a rule. The rule specifies that, for iteratively determining information about the one or more rectangular slices, a variable indicating a tile index is updated only for slices having indices that are smaller than a value equal to a number of slices in the video picture minus 1.

A network management system manages the operation of a home security system in a communication network, such as a mesh network. The home security system can include multiple components such as a camera, a lighting device, a security alarm, a doorbell switch and doorbell chime, and a fingerprint sensor, which connect with the communication network to perform various operations. The network management system monitors environmental parameters of the communication network, such as parameters associated with the access points and components of the home security system, determines an access point to which a component of the home security system is to be connected for efficient operation of the home security system, and connects the component to the communication network via the determined access point.

A network management system manages the operation of a home security system in a communication network, such as a mesh network. The home security system can include multiple components such as a camera, a lighting device, a security alarm, a doorbell switch and doorbell chime, and a fingerprint sensor, which connect with the communication network to perform various operations. The network management system monitors environmental parameters of the communication network, such as parameters associated with the access points and components of the home security system, determines an access point to which a component of the home security system is to be connected for efficient operation of the home security system, and connects the component to the communication network via the determined access point.

Use of multiple sensors to determine whether motion of an object is occurring in an area is described. In one aspect, an infrared (IR) sensor can be supplemented with a radar sensor to determine whether the determined motion of an object is not a false positive.

Use of multiple sensors to determine whether motion of an object is occurring in an area is described. In one aspect, an infrared (IR) sensor can be supplemented with a radar sensor to determine whether the determined motion of an object is not a false positive.

A system and method for providing quality control in immersive video during pausing of a video streaming session. In one embodiment, a paused video frame may comprise a plurality of mixed quality video tiles depending on user gaze vector information. Under pause control, the video quality of all tiles of the paused video frame is equalized such that it is of same value for all the video tiles, which may be the video quality of the tiles presented in a viewport of the client device. The paused video frame having the same quality tiles throughout is used as a replacement video frame, which is presented to the client device player for decoding and displaying instead of the mixed quality video frame while the streaming session is paused.

Embodiments include a system, method, and computer program product that enable secure access to cameras in smart buildings. Some embodiments control outbound video from an environment such as a local network through an intelligent on-event video pushing mechanism. The local intelligent on-event video pushing mechanism hides the IP address of a source video camera, transcodes the video to a reduced size for wide area distribution, and pushes video to a recipient upon an event triggered received within the local environment (e.g., the local network.) Embodiments enable a remote video client on the far-side of the local network firewall to view the video streams of cameras on the near-side of the local network firewall when an event or trigger occurs.