Euclid Discoveries, LLC

Christopher Weed

Nigel Lee

Dane P Kottke

Jeyun Lee

Sangseok Park

Myo Tun

Kenneth Goeller

John J Guo

Richard Wingard

Justin Kwan

Caroline Wingard

Example embodiments of the disclosure may provide a recompressor system that configures dynamic Video Ad Serving Template (VAST) tags enabling seamless delivery of mezzanine-level quality video ads of the highest resolution compatible with the user's system requirements. Aspects of the disclosure relate to reprocessing of received VAST tag, parsing the tag to identify the location of the video of highest resolution, accessing the video of highest resolution and forwarding it to a compression engine (Euclid's in this case). Compression engine re-compresses video in one or more formats and sends back location(s) of the videos. Receiving back one or more video locations and an updated VAST tag and forwarding that.

Method for dynamic video compression in an ad delivery ecosystem

Perceptual statistics are used to compute importance maps that indicate which regions of a video frame are important to the human visual system. Importance maps may be generated from encoders that produce motion vectors and employ motion estimation for inter-prediction. The temporal contrast sensitivity function (TCSF) may be computed from the encoder's motion vectors. Quality metrics may be used to construct a true motion vector map (TMVM), which refines the TCSF. Spatial complexity maps (SCMs) can be calculated from simple metrics (e.g. block variance, block luminance, SSIM, and edge detection). Importance maps with TCSF, TMVM, and SCM may be used to modify the standard rate-distortion optimization criterion for selecting the optimum encoding solution. Importance maps may modify encoder quantization. The spatial information for the importance maps may be provided by a lookup table based on block variance, where negative and positive spatial QP offsets for block variances are provided.

Perceptual optimization for model-based video encoding

Perceptual statistics may be used to compute importance maps that indicate which regions of a video frame are important to the human visual system. Importance maps may be applied to the video encoding process to enhance the quality of encoded bitstreams. The temporal contrast sensitivity function (TCSF) may be computed from the encoder's motion vectors. Motion vector quality metrics may be used to construct a true motion vector map (TMVM) that can be used to refine the TCSF. Spatial complexity maps (SCMs) can be calculated from metrics such as block variance, block luminance, SSIM, and edge strength, and the SCMs can be combined with the TCSF to obtain a unified importance map. Importance maps may be used to improve encoding by modifying the criterion for selecting optimum encoding solutions or by modifying the quantization for each target block to be encoded.

Continuous block tracking (CBT) tracks macroblock locations over reference frames to produce better inter-predictions than conventional block-based motion estimation/compression. CBT includes frame-to-frame tracking, estimating motion from a frame to a previous frame, and continuous tracking, related frame-to-frame motion vectors to block tracks. Frame-to-frame tracking may include block based or hierarchical motion estimations. CBT combined with enhanced predictive zonal search may create unified motion estimation. Accumulated CBT results may form trajectories for trajectory-based CBT predictions. Metrics measuring continuous track and motion vector quality can assess relative priority of CBT prediction against non-tracker-based predictions and to modify encoding choices. Continuous tracks can be analyzed for goodness-of-fit to translational motion models, with outliers removed from encoding. Translational motion models can be extended to entire frames in adaptive picture type selection. Outputs from CBT used in look-ahead processing, via look-ahead tracking, may provide rate control and scene change detection for the current frame being encoded.

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Sudbury, MA, United States of America

Christopher Weed