UAV Communication Bandwidth Optimization for Video Streaming

Adaptive bitrate streaming system that improves video quality by selectively requesting higher bitrate segments for complex scenes based on available bandwidth, while maintaining smooth playback and minimizing buffering. The system determines scene complexity and dynamically adjusts bitrate requests to prioritize high-motion content, enabling better video quality without compromising stability.

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A method for adaptive bitrate streaming that selects a target version of encoded video content based on display properties rather than decoder capabilities, and streams it even when network bandwidth is sufficient to support higher quality versions. The target version is encoded to a target value of an encoding attribute, such as frame size, that is less than the maximum value supported by the client device.

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Predicting bitrate selection for streaming media using machine learning models to improve adaptive bitrate streaming performance. The technology employs supervised learning to train models that predict future download speeds and buffer states, enabling more accurate bitrate selection and reduced rebuffering.

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Adaptive bitrate (ABR) streaming method for video content delivery over HTTP networks, where a receiver requests video segments based on available bandwidth rather than buffer levels. The method involves probing available bandwidth by requesting enhancement layer segments with decreasing priorities, and adjusting subsequent base layer segment requests based on the received enhancement layer segments.

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A streaming assistance system that optimizes media content delivery by dynamically switching between multiple network connections, including satellite and terrestrial links, to aggregate bandwidth and reduce latency. The system identifies media fragments expected to be requested by the client device and prefetches them in parallel using both network links, enabling seamless playback even in areas with limited connectivity.

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A network monitoring system that dynamically establishes bandwidth allocation policies across various network environments through transferable reinforcement learning, enabling smooth operation of quality-of-experience (QoE) centered IoT applications. The system employs reinforcement learning to optimize bandwidth allocation based on real-time network conditions, ensuring QoE meets predefined targets while adapting to changing network environments.

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Predicting bitrate selection for streaming media using machine learning models to improve adaptive bitrate streaming performance. The system employs supervised learning models, such as random forest decision trees, to predict future download speeds and buffer behavior based on historical data and streaming parameters. The models can be integrated into streaming devices or run remotely in the cloud to optimize bitrate selection and prevent rebuffering.

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Adaptive bitrate streaming system that improves video quality by selectively requesting higher bitrate segments for complex scenes, even if the user's available bandwidth is insufficient to support them. The system determines scene complexity and dynamically adjusts bitrate requests to prioritize high-complexity segments, enabling better video quality without compromising playback stability.

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A method for adaptive bitrate streaming of digital video that improves quality selection by analyzing buffer data and download rates in a range-based manner, rather than relying on a single bandwidth estimate. The method segments the video into ranges and evaluates the buffer data and download rates for each range to determine the optimal quality for streaming. This approach enables more accurate quality selection and reduced rebuffering delays compared to traditional adaptive bitrate methods.

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A wireless video transmission system that employs a hierarchical data structure to represent video data, comprising a base layer and one or more enhancement layers with associated residual data. The base layer provides a coarse rendition of the input signal, while the enhancement layers enhance the base layer to achieve high-quality video. The system dynamically adjusts the transmission rate of the enhancement layers based on channel conditions to minimize latency while maintaining a base level of quality.

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A technique to improve multimedia streaming efficiency by dynamically increasing resolution of previously streamed segments without requiring re-streaming. When streaming video, instead of always adjusting bitrate based on available bandwidth, segments are initially streamed at lower resolution. Later segments are streamed at higher resolution if bandwidth allows. To avoid wasting bandwidth if the viewer skips ahead, segments are also streamed at lower resolution than optimal. Later, pixels are added to upgrade resolution only for viewed segments. This allows increasing resolution without re-streaming and prevents wasting bandwidth on skipped segments.

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A system and method for adaptive media playback that improves quality by dynamically adjusting bitrate based on multiple factors beyond network throughput, including decode performance, render performance, player overhead, and system resources. The system continuously monitors playback performance and adjusts bitrate requests to ensure optimal quality, rather than relying solely on network bandwidth.

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Adjusting video transmission rate during segment transmission to prevent packet loss and maintain video quality. When network conditions deteriorate during a segment, the transmission rate is reduced for the entire segment, rather than waiting for the current segment to complete. The client device is instructed to decode and present the lower bitrate segment at a faster rate, skipping the already presented higher bitrate frames.

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Adaptive bitrate streaming system that improves video quality by selectively requesting higher bitrate segments for complex scenes based on available bandwidth, while maintaining smooth playback. The system determines scene complexity and dynamically adjusts bitrate requests to prioritize high-motion content, enabling better video quality without compromising stability.

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A remote video transmission method that dynamically adjusts encoding bit rate based on client bandwidth and packet loss, and coordinates server and client capabilities to achieve smooth and high-quality video transmission. The method includes the server sending video frames to the client, receiving client feedback on packet loss and bandwidth, predicting its own bandwidth, and adjusting its encoding bit rate accordingly. The server also monitors client decoding and rendering capabilities and adjusts its frame rate accordingly.

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Optimizing video streaming to reduce stalls and improve playback in adaptive bitrate (ABR) video. The method involves prioritizing frame transmission order within a video chunk. Frames are ordered with I-frames first, followed by forward-predicted P-frames, then reference B-frames, and finally optional non-reference b-frames. This prioritization ensures critical reference frames are received first, even if the chunk is truncated before all frames. If a stall risk is detected during chunk download, the player requests the next chunk and stops the current one mid-transfer. This allows using in-flight frames to extend playback without waiting for the full chunk.

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A method for dynamically adapting video streaming profiles based on predicted network conditions. The method involves predicting network conditions using session features, selecting a subset of available profiles based on the predicted conditions, and providing a profile ladder that restricts the client to using the selected subset of profiles. The profile ladder is dynamically updated based on playback conditions during the session.

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Synchronizing playback of media content across multiple devices to prevent buffering delays and quality issues. The method involves coordinating the streaming rates to match device buffer speeds. If a device falls behind, the server lowers the quality of the stream to match. This ensures all devices stay synchronized during playback.

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A system and method for managing video streaming traffic in a network to maintain Quality of Experience (QoE) across multiple service categories. The system determines a set of service categories, maps traffic flows to each category, and measures QoE and bandwidth use. It adjusts minimum bandwidth intents for categories not meeting their targets, allocates bandwidth based on the adjusted intents, and shapes traffic flows to maintain QoE across categories. The system manages video streaming traffic growth to prevent congestion while maintaining acceptable QoE for other service categories.

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Adaptive streaming service for multiple narrowband wireless networks that dynamically selects between TCP and UDP protocols and determines redundant data sizes based on network conditions to provide stable and energy-efficient video streaming in environments with limited bandwidth and packet loss.

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A system for encoding video signals that optimizes bit rate control by dynamically allocating bit rates between two encoders based on scene complexity. The system includes a first encoder and a second encoder, each with its own rate control unit, and an adaptive rate control unit that monitors scene complexity and adjusts the bit rates accordingly. The second encoder can also receive a reference stream from the first encoder to enable more efficient encoding.

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Generating adaptive bitrate video streaming manifests optimized for specific device resolutions to deliver the best possible video quality. The manifest contains a superset of representations including the highest quality streams for each device resolution. When a playback request is received, the manifest is dynamically filtered to contain only the optimal subset of representations for that device resolution. This allows devices to transition to the highest quality they can support based on their resolution.

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A control device for managing network bandwidth in a dynamic environment with multiple types of applications. The device acquires application information at multiple time points for each session, predicts Quality of Experience (QoE) based on this information and network conditions, and dynamically adjusts bandwidth allocation for each session at multiple time points to minimize QoE degradation.

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A media streaming system that enables efficient transmission of multimedia content over networks by shifting bitrate adaptation control from the client to the server. The system employs server-push technology to deliver media content in temporal segments at varying bitrates, with the server adapting the bitrate based on client reception situation updates. This approach reduces upstream bandwidth consumption, enables fair distribution of available transmission bandwidth among multiple clients, and minimizes latency compared to traditional client-pull techniques.

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Transmission method, system, and control device for vehicle-mounted cameras that dynamically allocates bandwidth based on camera importance and estimated network capacity to prioritize critical visual information for remote monitoring and control.

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Network that can manipulate bandwidth in the network in such a way to provide video streams to streaming clients at a guaranteed bandwidth. The network includes a bridge unit coupled to a bridge controller and a streaming controller arranged to control streaming settings.

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A method for adaptive bitrate streaming that optimizes network resource utilization by dynamically adjusting buffer sizes and priorities based on client characteristics and video content requirements. The method records client bandwidth speeds to determine initial bitrates, configures buffer sizes based on movie types, and prioritizes streams based on buffer states and frame sizes. Bitrate switching is performed in real-time based on buffer conditions and download times, with shared stream buffers enabled through a P2P protocol.

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A system and method for adaptively varying the quality of a video stream based on available bandwidth and decoder capabilities. The system encodes video data in a hierarchical arrangement with a base layer and multiple enhancement layers, each comprising sub-layers of enhancement data. The enhancement data is quantized and allocated to sub-layers based on notional quantization levels, enabling partial download and decoding of enhancement layers without requiring complete download of each layer. This allows decoders to adaptively select and decode enhancement layers based on available bandwidth and capabilities, enabling optimal video quality delivery.

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A QoE-driven VR video adaptive acquisition and transmission method that optimizes multi-user quality of experience (QoE) in VR video transmission by jointly considering uplink and downlink transmission processes. The method uses QoE as a guiding factor to adaptively collect and transmit VR video, incorporating user feedback and network conditions to improve overall QoE.

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A method for adaptive video streaming that enables dynamic quality adjustment based on network conditions, device capabilities, and user preferences. The method encodes video content using a tiered hierarchy of reconstruction data, where each tier represents a different quality level. The streaming server selectively transmits reconstruction data to the decoder, varying the quality level in real-time to match the current network conditions and device capabilities. This allows for seamless quality adaptation, efficient bandwidth utilization, and improved user experience.

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A method for adaptive video streaming that optimizes quality-of-experience (QoE) by incorporating QoE estimation into client-side decision-making. The method generates QoE prediction parameters at the server-side and transmits them to the client, where they are combined with real-time network and device information to estimate actual user QoE. This QoE estimate is then used to select the next video segments, enabling smart adaptive streaming that balances bandwidth efficiency with visual quality and smoothness.

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A method for adaptive bitrate video streaming that selects a target version of encoded video content based on display properties rather than decoder capabilities. The method identifies a target version encoded to a specific value of an encoding attribute, such as frame size, and determines if the network bandwidth is sufficient to stream and display that version. If available, the method prioritizes streaming the target version even if higher bitrate versions could be streamed without interruption.

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A video streaming system that reduces playback dropouts when network conditions degrade. The system employs two parallel video streams: a primary stream that requests sequential blocks at playback rate, and a secondary stream that requests blocks ahead of time and buffers them. When the primary stream encounters network issues, the secondary stream's buffered blocks are seamlessly switched to maintain continuous playback.

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Recording and playing back video chunks in a different order to improve video quality and reliability in adaptive bitrate streaming. The technique involves recording the chunks with intra frames first followed by inter frames, instead of the natural order. This allows partial chunk playback if some frames are missed, as the intra frames can still be decoded on their own. It also reduces stalling and buffering by avoiding long sequences of missing inter frames. The player switches between chunks less frequently since the intra frames can bridge gaps.

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Optimizing streaming bitrate during multiclient streaming sessions based on display profiles associated with client media receivers. The system establishes display profile-dependent bandwidth allotment thresholds for client media receivers during a multiclient streaming session, enabling differentiated stream quality between devices with varying display demands while reducing server processing loads.

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Network management system for optimizing perceptual playback quality of media content across multiple client devices. The system dynamically adjusts shared network resources such as bandwidth based on an aggregate quality of experience (QoE) metric that reflects the distribution of QoE levels across all client devices. This enables coordinated management of perceptual playback quality across multiple devices, preventing individual devices from misappropriating network resources and optimizing overall QoE.

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Method for adaptive bitrate streaming that reduces playback disturbances by buffering hierarchical layers of encoded data, including a base layer and an enhancement layer, and decoding the base layer while continuing to receive and buffer the enhancement layer.

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A method for adaptive bitrate streaming that improves bandwidth efficiency and visual stability by prioritizing reference frames in a video chunk, followed by non-reference frames, and enabling partial chunk playback with a defined loss tolerance level. The method exploits the temporal dependency of inter-frame coding protocols to ensure that reference frames are received before non-reference frames, allowing for more continuous quality transitions and reduced quality switches.

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A system for encoding video signals that optimizes bit rate control by dividing the encoding process into two stages. The first stage uses a temporal correlation-based encoder to generate a base encoded stream, while the second stage uses a spatial correlation-based encoder to generate a secondary encoded stream. The system dynamically adjusts the bit rates for each stage based on the complexity of the video content and the amount of default data generated by the first stage.

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A content streaming system dynamically manages adaptive bitrate streaming bundles by utilizing an efficiency matrix that associates metadata with available bitrate encodings and formats. The system dynamically adjusts bitrate manifests based on network conditions, client attributes, content attributes, and other factors to optimize content delivery.

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Method for real-time bitrate allocation to multiple signals in a multiplexed bundle, comprising: deriving complexity information for each signal from a single image; generating a model of the bitrate-quality curve for each signal based on the complexity information; and dynamically allocating bitrate to each signal in real-time based on the model, while maintaining a constant overall bitrate for the bundle.

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A method for optimizing multimedia content delivery in wireless networks through adaptive rate control. The method involves a proxy server intercepting client requests for multimedia content and dynamically selecting lower-bitrate versions of content segments based on their complexity and the available network bandwidth. The proxy server generates optimized requests to the content server, which then delivers the selected segments to the client. This approach enables efficient bandwidth utilization while maintaining acceptable video quality, particularly in networks with fluctuating bandwidth conditions.

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A system for optimizing video transmission in multi-camera surveillance installations with shared network uplinks. The system dynamically allocates available bandwidth among cameras based on their predicted bitrate requirements, and adjusts encoder parameters to maximize video quality while staying within allocated bandwidth limits. The system uses historical bandwidth measurements and predictive modeling to forecast future bandwidth availability, enabling proactive bitrate management and minimizing video loss and latency.

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A system for adaptive bitrate streaming that improves video quality and reduces rebuffering by incorporating a timeout function, buffer offset function, and startup function into the main mapping function. The timeout function interrupts chunk downloads that exceed a threshold, switching to a lower variant to prevent rebuffering. The buffer offset function adjusts the buffer level threshold for variant selection, and the startup function uses capacity estimation for initial variant selection. The system optimizes video quality and reduces rebuffering events in both live and recorded video streaming.

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