Samsung Electronics Co., Ltd.

Ankur Saxena

Madhukar Budagavi

Hossein Najaf-Zadeh

Felix Carlos Fernandes

Abhishek Nagar

Gaurav Srivastava

Zhu Li

Kong Posh Bhat

Esmaeil Faramarzi

Zhan Ma

Andrew Joseph Dickerson

Wang Lin Lai

Karthikeyan S Vadivel

Jeffrey Wilkinson

John Furton

Guoxin Jin

Serhat Bucak

A user equipment (UE) includes a receiver, display, and processor. The receiver is configured to receive a data stream including a plurality of frames. The data stream includes a region of interest in a key frame of the plurality of frames. The display is configured to display a portion of a frame of the plurality of frames. The processor is configured to perform an action to focus a current view of the UE to the region of interest in the key frame. Each frame of the plurality of frames includes a plurality of images stitched together to form a stitched image. The stitched image for at least one frame of the plurality of frames includes at least one high dynamic range (HDR) image and at least one standard dynamic range (SDR) image.

Generating and transmitting metadata for virtual reality

A user equipment (UE) includes a receiver, at least one sensor, and a processor. The receiver is configured to receive a bit stream including at least one encoded image and metadata. The sensor is configured to determine viewpoint information of a user. The processor is configured to render the at least one encoded image based on the metadata and the viewpoint.

Method and apparatus for view-dependent tone mapping of virtual reality images

A user equipment includes a modem receives a compressed bitstream and metadata. The UE also includes a decoder that decodes the compressed bitstream to generate an HDR image, an inertial measurement unit that determines viewpoint information based on an orientation of the UE, and a graphics processing unit (GPU). The GPU maps the HDR image onto a surface and renders a portion of the HDR image based on the metadata and the viewpoint information. A display displays the portion of the HDR image.

Method and apparatus for creating, streaming, and rendering HDR images

A video processing unit and method for region adaptive smoothing. The image processing unit includes a memory and one or more processors. The one or processors are operably connected to the memory and configured to stitch together a plurality of video frames into a plurality of equirectangular mapped frames of a video. The one or processors are configured to define a top region and a bottom region for each of the equirectangular mapped frames of the video; perform a smoothing process on the top region and the bottom region for each of the equirectangular mapped frames of the video; and encode the smoothed equirectangular mapped frames of the video.

Coding of 360 degree videos using region adaptive smoothing

A user equipment (UE) includes a receiver and a processor. The receiver is configured to receive a standard dynamic range (SDR) image and metadata related to an HDR image. The processor is configured to identify relevant portions of the SDR image to be enhanced based on the metadata related to the HDR image. The processor is also configured to increase an intensity of the relevant portions of the SDR image to create an enhanced SDR image. The processor is also configured to output the enhanced SDR image to a display.

Method and apparatus for enhancing images via white pop-out

To reduce communication costs and computational complexity, only a subset of ranked SIFT points within a query image for a visual search request is transmitted to the visual search server in each iteration of an incremental search. For each candidate match, a flag identifying the matching points is returned by the server for use in computing holistic (e.g., histogram) information for a bounding box within the query image including the matching points. Distance from that query image holistic information is used to reject images from a short list used for a subsequent iteration, if any. If all images are rejected or a match criteria is met during one iteration, the search may terminate early without consideration of remaining SIFT points.

Incremental visual query processing with holistic feature feedback

A method comprises computing a color factor value indicating an amount of color gradients in at least one color channel from the query image. The method comprises combining the color-keypoints with the gray-keypoints when the color factor value is greater than a threshold. A method for performing a visual search comprises extracting a plurality of local descriptors from a query image and then selecting a subset of them based on various criteria's such as visual meaning score. A method comprises aggregating each mean vector for each visual codeword from distances between each visual codeword and local descriptors. The method comprises aggregating variance vector for each visual codeword from the distance between each visual codeword, and local descriptors. The method comprises transmitting aggregated mean vector information and aggregated variance vector information to a search server for efficient image retrieval.

Apparatus and method for performing visual search

An apparatus and method for video fingerprinting are provided. The method includes, for each frame of a video sequence including a plurality of frames, removing a portion of the frame, dividing a remaining portion of the frame into blocks, dividing each block into sub-blocks, computing a block level feature as a mean of pixels in each sub-block within the block, concatenating all block level features in the frame, and concatenating features of all frames in the video sequence.

Apparatus and method for robust low-complexity video fingerprinting

A method and apparatus encode and decode video by determining whether to use discrete cosine transform (DCT) and DST for each of the horizontal and vertical transforms. During encoding, an intra-prediction is performed based on an intra-prediction mode determined for an M&#xd7;N input image block to obtain an M&#xd7;N intra-prediction residue matrix (E). Based on the intra-prediction mode, each of a horizontal transform and a vertical transform is performed using one of DCT and DST according to the intra-prediction mode. During decoding, the intra-prediction mode is determined from an incoming video bitstream. The M&#xd7;N transformed coefficient matrix of the error residue is obtained from the video bitstream using an inverse quantizer. Based on the intra prediction mode, one of DCT and DST is performed for each of an inverse vertical transform and an inverse horizontal transform.

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Dallas, TX, United States of America

Ankur Saxena