The present disclosure is related to video processing technologies and discloses a method and a device for transcoding a video. The method includes: reconstructing an existing semantic segmentation model based on a processing layer supported by a TensorRT engine; loading a reconstructed semantic segmentation model into the TensorRT engine to generate a TensorRT acceleration model; performing semantic segmentation on a video frame image through the TensorRT acceleration model to generate a multi-level ROI of the video frame image; using different transcoding rates to transcode the multi-level ROI and other regions of the video frame image respectively.

The present disclosure is related to video processing technologies and discloses a method and a device for transcoding a video. The method includes: reconstructing an existing semantic segmentation model based on a processing layer supported by a TensorRT engine; loading a reconstructed semantic segmentation model into the TensorRT engine to generate a TensorRT acceleration model; performing semantic segmentation on a video frame image through the TensorRT acceleration model to generate a multi-level ROI of the video frame image; using different transcoding rates to transcode the multi-level ROI and other regions of the video frame image respectively.

Video streams, either in form of on-demand streaming or live streaming, usually have to be transcoded based on the characteristics of clients' devices. Transcoding is a computationally expensive and time-consuming operation; therefore, streaming service providers currently store numerous transcoded versions of the same video to serve different types of client devices. Due to the expense of maintaining and upgrading storage and computing infrastructures, many streaming service providers recently are becoming reliant on cloud services. However, the challenge in utilizing cloud services for video transcoding is how to deploy cloud resources in a cost-efficient manner without any major impact on the quality of video streams. To address this challenge, in this paper, the Cloud-based Video Streaming Service (CVSS) architecture is disclosed to transcode video streams in an on-demand manner. The architecture provides a platform for streaming service providers to utilize cloud resources in a cost-efficient manner and with respect to the Quality of Service (QoS) demands of video streams. In particular, the architecture includes a QoS-aware scheduling method to efficiently map video streams to cloud resources, and a cost-aware dynamic (i.e., elastic) resource provisioning policy that adapts the resource acquisition with respect to the video streaming QoS demands. Simulation results based on realistic cloud traces and with various workload conditions, demonstrate that the CVSS architecture can satisfy video streaming QoS demands and reduces the incurred cost of stream providers up to 70%.

The present disclosure discloses a method and device for transcoding a video, which belongs to the video processing technology. The method includes: acquiring a target frame image of a video to be transcoded, and generating a global feature map of the target frame image based on a feature extraction module of a semantic segmentation model; performing feature segmentation on the global feature map based on a feature segmentation module of the semantic segmentation model, and determining a multi-level ROI of the target frame image; and using different transcoding rates to transcode the multi-level ROI and other regions of the target frame image respectively.

The present disclosure discloses a method and device for transcoding a video, which belongs to the video processing technology. The method includes: acquiring a target frame image of a video to be transcoded, and generating a global feature map of the target frame image based on a feature extraction module of a semantic segmentation model; performing feature segmentation on the global feature map based on a feature segmentation module of the semantic segmentation model, and determining a multi-level ROI of the target frame image; and using different transcoding rates to transcode the multi-level ROI and other regions of the target frame image respectively.

A video streaming service may include a segmentation component that provides segment metadata that indicates starting locations for a plurality of segments of video content that are produced during transcoding of the video content. The segment metadata may be sent to a first transcode server and a second transcode server to allow alignment of segmentations between the first transcode server and the second transcode server. This may allow transcoding of the video content to be seamlessly switched from the first transcode server to the second transcode server, during transmission of the video content, without causing interruption of playback. The first transcode server and the second transcode server may also operate in parallel to produce different versions of the video content, such as versions encoded using different codecs. A video player may seamlessly switch between these different codec versions without causing interruption of playback.

A video streaming service may include a segmentation component that provides segment metadata that indicates starting locations for a plurality of segments of video content that are produced during transcoding of the video content. The segment metadata may be sent to a first transcode server and a second transcode server to allow alignment of segmentations between the first transcode server and the second transcode server. This may allow transcoding of the video content to be seamlessly switched from the first transcode server to the second transcode server, during transmission of the video content, without causing interruption of playback. The first transcode server and the second transcode server may also operate in parallel to produce different versions of the video content, such as versions encoded using different codecs. A video player may seamlessly switch between these different codec versions without causing interruption of playback.

Systems, methods and computer program products for high-performance, low latency start-up of large shared media files. A method for low latency startup with low defect playback commences upon identifying a first media file having a first format to be converted to a second media file having a second format. A scheduler divides the first media file into multiple partitions separated by partition boundaries. The method continues by converting the partitions into respective converted partitions that comport with the second format. Determinations as to the position of the partition boundaries is made based on measurable conditions present at a particular moment in time. Different formats receive different treatment based on the combination of characteristics of the first format, characteristics of the second format, as well as on characteristics of measurable conditions present at the moment in time just before conversion of a segment.

Systems, methods and computer program products for high-performance, low latency start-up of large shared media files. A method for low latency startup with low defect playback commences upon identifying a first media file having a first format to be converted to a second media file having a second format. A scheduler divides the first media file into multiple partitions separated by partition boundaries. The method continues by converting the partitions into respective converted partitions that comport with the second format. Determinations as to the position of the partition boundaries is made based on measurable conditions present at a particular moment in time. Different formats receive different treatment based on the combination of characteristics of the first format, characteristics of the second format, as well as on characteristics of measurable conditions present at the moment in time just before conversion of a segment.

A medical telepresence system comprising: an interface to receive a plurality of data feeds from a live medical procedure, at least one data feed comprising a video signal capturing the live medical procedure; a hierarchical encoder to encode the plurality of data feeds using a first tier-based hierarchical data coding scheme, wherein encoded data from the hierarchical encoder is decodable by a first set of computing devices for viewing, the first set of computing devices being communicatively coupled to the hierarchical encoder using a first network connection; a transcoder to convert from the first tier-based hierarchical data coding scheme to a second tier-based hierarchical data coding scheme, wherein encoded data from the transcoder is receivable by a second set of computing devices for viewing, the second set of computing devices being communicatively coupled to the transcoder using a second network connection, the second network connection being of a lower quality than the first network connection; and a recorder to store the output of the hierarchical encoder as a set of tier-based files for later retrieval, wherein each of the set of tier-based files represent different levels of quality.