Abstract: Systems, apparatuses, and methods for generating a model for determining a quantization strength to use when encoding video frames are disclosed. A pre-encoder performs multiple encoding passes using different quantization strengths on a portion or the entirety of one or more pre-processed video frames. The pre-encoder captures the bit-size of the encoded output for each of the multiple encoding passes. Then, based on the multiple encoding passes, the pre-encoder generates a model for mapping bit-size to quantization strength for encoding video frames or portion(s) thereof. When the encoder begins the final encoding pass for one or more given video frames or any portion(s) thereof, the encoder uses the model to map a preferred bit-size to a given quantization strength. The encoder uses the given quantization strength when encoding the given video frame(s) or frame portion(s) to meet a specified bit-rate for the encoded bitstream.

Abstract: System, methods, and other embodiments described herein relate to improving trajectory forecasting in a device. In one embodiment, a method includes, in response to receiving sensor data about a surrounding environment of the device, identifying an object from the sensor data that is present in the surrounding environment. The method includes determining category probabilities for the object, the category probabilities indicating semantic classes for classifying the object and probabilities that the object belongs to the semantic classes. The method includes forecasting trajectories for the object based, at least in part, on the category probabilities and the sensor data. The method includes controlling the device according to the trajectories.

Abstract: A technique for determining a quality value for a subject block of encoded video is provided. Contributing blocks, of the same frame and/or different frames of the subject block, are determined by identifying blocks likely to be a part of the same moving object or background as the subject block. A spatial and/or temporal filter is then applied to the quality values of the contributing blocks and an initial quality value of the subject block. With a spatial filter, quality values for contributing blocks from the same frame are combined and used to modify the quality value of the subject block. With a spatial filter, a temporal characteristic quality value for contributing blocks of one or more other frames (such as the immediately previous frame) is determined and then combined with a quality value representative of the subject block.

Abstract: A system and method for dynamically changing encode quality at a block level based on runtime pre-encoding analysis of content in a video stream. A video encoder continuously analyzes the content during runtime, and collects statistics and/or characteristics of the content before encoding it. This classifies the block among pre-defined categories of content, where every category has its own compression parameters.

Abstract: A mobile robot can be caused to move according to a planned trajectory. The mobile robot can be a vehicle. Information about agents in an environment of the mobile robot can be received from sensors. At a first time, a spatiotemporal graph can be produced. The spatiotemporal graph can represent relationships among the agents in the environment. The mobile robot can be one of the agents in the environment. Information from the spatiotemporal graph can be input to neural networks to produce information for a mixture of affine time-varying systems. The mixture of affine time-varying systems can represent an evolution of agent states of the agents. Using the mixture of affine time-varying systems and information associated with the first time, a prediction of the agent states at a second time can be calculated. The mobile robot can be caused to move according to the planned trajectory determined from the prediction.

Abstract: Techniques are provided herein for processing video data. The techniques include generating predicted macroblock coding modes for a set of macroblocks of a frame, assigning quantization parameters to the macroblocks based on the predicted macroblock coding modes, and encoding the set of macroblocks based on the quantization parameters.

Abstract: Systems, apparatuses, and methods for block type prediction leveraging block-based pixel activities are disclosed. A pre-encoder generates predictions of block types for the blocks of a video frame based on associated pixel activities. For each block, the pre-encoder calculates the difference between the pixel activities of the block of a current frame and the pixel activities of a corresponding block of a previous video frame. If the difference is less than a first threshold, the pre-encoder predicts that the block will be a skip block. If the difference is in between the first threshold and a second threshold, the pre-encoder predicts that the block will be a P-block. Otherwise, if the difference is greater than the second threshold, then the pre-encoder predicts that the block will be an I-block. The pre-encoder uses the predictions to select quantization parameter (QP) ranges for encoding the blocks of the video frame.

Abstract: A display system modifies display cycles of one or more displays to perform a system operation while avoiding visual perturbations at the one or more displays. The display system modifies, synchronizes, or both, blanking periods of the one or more displays such that blanking periods equal or exceed a blackout duration and overlap for at least the blackout duration. Then the system performs the system operation during an overlapping portion of the one or more blanking periods, where the system operation reduces availability of display data at the one or more displays.

Abstract: A processing device for executing a machine learning neural network operation includes memory and a processor. The processor is configured to receive input data at a layer of the machine learning neural network operation, receive a plurality of sorted filters to be applied to the input data, apply the plurality of sorted filters to the input data to produce a plurality of different feature maps, compress the plurality of different feature maps according to a similarity of the feature maps relative to each other and store the plurality of different feature maps in the memory.

Abstract: A processing system analyzes pixel activity levels of blocks of a picture at a plurality of spatial scales and/or dynamic ranges to generate a multi-scale metric that indicates how bit allocation or assignment of a given quantization parameter (QP) will affect the perceptual quality of the block. Blocks that have similar multi-scale metrics are likely to be visually similar and to benefit from similar bit allocations or QPs. Based on the multi-scale metric, an encoder encodes each block of the picture with a QP and/or a number of bits.

Abstract: Systems, apparatuses, and methods for implementing spatial block-level pixel activity extraction optimization leveraging motion vectors are disclosed. Control logic coupled to an encoder generates block-level pixel activity metrics for a new frame based on the previously calculated block-level pixel activity data from a reference frame. A cost is calculated for each block of a new frame with respect to a corresponding block of the reference frame. If the cost is less than a first threshold, then the control logic generates an estimate of a pixel activity metric for the block which is equal to a previously calculated pixel activity metric for a corresponding block of the reference frame. If the cost is greater than the first threshold but less than a second threshold, an estimate of the pixel activity metric is generated by extrapolating from the previously calculated pixel activity metric.

Abstract: Systems, apparatuses, and methods for using residual metrics for encoder rate control are disclosed. An encoder includes a mode decision unit for determining a mode to be used for generating a predictive block for each block of a video frame. For each block, control logic calculates a residual of the block by comparing an original version of the block to the predictive block. The control logic generates a residual metric based on the residual and based on the mode. The encoder's rate controller selects a quantization strength setting for the block based on the residual metric. Then, the encoder generates an encoded block that represents the input block by encoding the block with the selected quantization strength setting. Next, the encoder conveys the encoded block to a decoder to be displayed. The encoder repeats this process for each block of the frame.

Abstract: Systems, apparatuses, and methods for bit budgeting in video encode pre-analysis based on context and features are disclosed. A pre-encoder receives a video frame and evaluates each block of the frame for the presence of several contextual indicators. The contextual indicators can include memory colors, text, depth of field, and other specific objects. For each contextual indicator detected, a coefficient is generated and added with other coefficients to generate a final importance value for the block. The coefficients can be adjusted so that only a defined fraction of the picture is deemed important. The final importance value of the block is used to determine the bit budget for the block. The block bit budgets are provided to the encoder and used to influence the quantization parameters used for encoding the blocks.

Abstract: Systems, apparatuses, and methods for implementing spatial block-level pixel activity extraction optimization leveraging motion vectors are disclosed. Control logic coupled to an encoder generates block-level pixel activity metrics for a new frame based on the previously calculated block-level pixel activity data from a reference frame. A cost is calculated for each block of a new frame with respect to a corresponding block of the reference frame. If the cost is less than a first threshold, then the control logic generates an estimate of a pixel activity metric for the block which is equal to a previously calculated pixel activity metric for a corresponding block of the reference frame. If the cost is greater than the first threshold but less than a second threshold, an estimate of the pixel activity metric is generated by extrapolating from the previously calculated pixel activity metric.

Abstract: A method includes obtaining, at a data reduction module, metrics of a first block of an input video frame and a second block of a reference frame. The data reduction module includes an analysis module and a filter. A perceptual importance of the first block of the input video frame is determined at the analysis module using the metrics. An entropy of the input video frame provided to an encoder is adjusted at the filter of the data reduction module based on the perceptual importance of the first block of the input video frame.

Abstract: A processing system analyzes pixel activity levels of blocks of a picture at a plurality of spatial scales and/or dynamic ranges to generate a multi-scale metric that indicates how bit allocation or assignment of a given quantization parameter (QP) will affect the perceptual quality of the block. Blocks that have similar multi-scale metrics are likely to be visually similar and to benefit from similar bit allocations or QPs. Based on the multi-scale metric, an encoder encodes each block of the picture with a QP and/or a number of bits.

Abstract: Described is a system and method for dynamically changing encode quality at a block level based on runtime pre-encoding analysis of content in a video stream. A video encoder continuously analyzes the content during runtime, and collects statistics and/or characteristics of the content before encoding it. This classifies the block among pre-defined categories of content, where every category has its own compression parameters.

Abstract: A technique for determining a quality value for a subject block of encoded video is provided. Contributing blocks, of the same frame and/or different frames of the subject block, are determined by identifying blocks likely to be a part of the same moving object or background as the subject block. A spatial and/or temporal filter is then applied to the quality values of the contributing blocks and an initial quality value of the subject block. With a spatial filter, quality values for contributing blocks from the same frame are combined and used to modify the quality value of the subject block. With a spatial filter, a temporal characteristic quality value for contributing blocks of one or more other frames (such as the immediately previous frame) is determined and then combined with a quality value representative of the subject block.

Abstract: Techniques are provided herein for processing video data. The techniques include generating predicted macroblock coding modes for a set of macroblocks of a frame, assigning quantization parameters to the macroblocks based on the predicted macroblock coding modes, and encoding the set of macroblocks based on the quantization parameters.

Abstract: A processing system filters blocks of a picture to minimize a size and error of the blocks prior to encoding. A pre-processing module of the processing system measures characteristics of a plurality of blocks and evaluates the effects of applying each of a plurality of filters to the blocks prior to encoding in order to predict an increase in compressibility of blocks having similar characteristics that are filtered with each filter before being encoded, with the least impact on quality. The pre-processing module trains models to predict a size and error of blocks filtered with each filter based on block characteristics. The pre-processing module uses the models to calculate a cost in terms of size and error of applying each filter to a given block having certain characteristics. The pre-processing module then applies to the block the filter that is predicted to result in the best cost.