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    ENCODING AND DECODING IMAGES USING DIFFERENTIABLE JPEG COMPRESSION
    2.
    发明申请
    ENCODING AND DECODING IMAGES USING DIFFERENTIABLE JPEG COMPRESSION 有权

    公开(公告)号：US20250008132A1

    公开(公告)日：2025-01-02

    申请号：US18755150

    申请日：2024-06-26

    Applicant: NEC Laboratories America, Inc.

    Inventor： Biplob Debnath ,  Deep Patel ,  Srimat Chakradhar ,  Christoph Reich

    IPC: H04N19/33 ,  H04N19/124 ,  H04N19/176 ,  H04N19/186 ,  H04N19/625

    Abstract: Systems and methods are provided for encoding and decoding images using differentiable JPEG compression, including converting images from RGB color space to YCbCr color space to obtain a luminance and chrominance channels, and applying chroma subsampling to the chrominance channels to reduce resolution. The YCbCr image is divided into pixel blocks and a DCT is performed on the pixel blocks to obtain DCT coefficients. DCT coefficients are quantized using a scaled quantization table to reduce precision, and quantized DCT coefficients are encoded using lossless entropy coding, forming a compressed JPEG file decoded by reversing the lossless entropy coding to obtain quantized DCT coefficients, which are dequantized using the scaled quantization table to restore the precision. The dequantized DCT coefficients are converted back to a spatial domain using an IDCT, the chrominance channels are upsampled to original resolution, and the YCbCr image is converted back to the RGB color space.

    OPTIMIZING MULTI-CAMERA MULTI-ENTITY ARTIFICIAL INTELLIGENCE TRACKING SYSTEMS
    4.
    发明申请
    OPTIMIZING MULTI-CAMERA MULTI-ENTITY ARTIFICIAL INTELLIGENCE TRACKING SYSTEMS 有权

    公开(公告)号：US20240378892A1

    公开(公告)日：2024-11-14

    申请号：US18654620

    申请日：2024-05-03

    Applicant: NEC Laboratories America, Inc.

    Inventor： Iain Melvin ,  Alexandru Niculescu-Mizil ,  Deep Patel

    IPC: G06V20/52 ,  G06T7/292

    Abstract: Systems and methods for optimizing multi-camera multi-entity artificial intelligence tracking systems. Visual and location information of entities from video feeds received from multiple cameras can be obtained by employing an entity detection model and re-identification model. Likelihood scores that entity detections belong to an entity track can be predicted from the visual and location information. The entity detections predicted into entity tracks can be processed by employing combinatorial optimization of the likelihood scores by identifying assumptions from the likelihood scores, entity detections, and the entity tracks, filtering the assumptions with unsatisfiable problems to obtain a filtered assumptions set, and optimizing an answer set by utilizing the filtered assumptions set and the likelihood scores to maximize an overall score and obtain optimized entity tracks. Multiple entities can be monitored by utilizing the optimized entity tracks.

    MULTI-CAMERA ENTITY TRACKING TRANSFORMER MODEL
    6.
    发明申请
    MULTI-CAMERA ENTITY TRACKING TRANSFORMER MODEL 有权

    公开(公告)号：US20250148624A1

    公开(公告)日：2025-05-08

    申请号：US18934512

    申请日：2024-11-01

    Applicant: NEC Laboratories America, Inc.

    Inventor： Deep Patel ,  Iain Melvin ,  Alexandru Niculescu-Mizil

    IPC: G06T7/292 ,  G06T7/00 ,  G06T7/70

    Abstract: Systems and methods for a multi-entity tracking transformer model (MCTR). To train the MCTR, processing track embeddings and detection embeddings of video feeds obtained from multiple cameras to generate updated track embeddings with a tracking module. The updated track embeddings can be associated with the detection embeddings to generate track-detection associations (TDA) for each camera view and camera frame with an association module. A cost module can calculate a differentiable loss from the TDA by combining a detection loss, a track loss and an auxiliary track loss. A model trainer can train the MCTR using the differentiable loss and contiguous video segments sampled from a training dataset to track multiple objects with multiple cameras.

    ANALYTICS-AWARE VIDEO COMPRESSION FOR TELEOPERATED VEHICLE CONTROL
    9.
    发明公开
    ANALYTICS-AWARE VIDEO COMPRESSION FOR TELEOPERATED VEHICLE CONTROL 审中-公开

    公开(公告)号：US20240275983A1

    公开(公告)日：2024-08-15

    申请号：US18439341

    申请日：2024-02-12

    Applicant: NEC Laboratories America, Inc.

    Inventor： Biplob Debnath ,  Christoph Reich ,  Deep Patel ,  Srimat Chakradhar

    IPC: H04N19/146 ,  G06V20/40 ,  G06V20/58 ,  H04N19/124 ,  H04N19/154

    CPC classification number: H04N19/146 ,  G06V20/49 ,  G06V20/58 ,  H04N19/124 ,  H04N19/154

    Abstract: Systems and methods are provided for optimizing video compression for remote vehicle control, including capturing, capturing video and sensor data from a vehicle using a plurality of sensors and high-resolution cameras, analyzing the captured video to identify critical regions within frames of the video using an attention-based module. Current network bandwidth is assessed and future bandwidth availability is predicted. Video compression parameters are predicted based on an analysis of the video and an assessment of the current network bandwidth using a control network, and the video is compressed based on the predicted parameters with an adaptive video compression module. The compressed video and sensor data is transmitted to a remote-control center, and received video and sensor data is decoded at the remote-control center. The vehicle is autonomously or remotely controlled from the remote-control center based on the decoded video and sensor data.

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