Mitsubishi Electric Research Laboratories, Inc.

Rca Thomson Licensing Corp.

Mitsubishi Electric Research Labs.

Mitsubishi Electric Information Technology Center America, Inc.

Sarnoff Corporation

Thomson Multimedia S.a.

Thomson Licensing S.a.

Sharp Corporation

Mitsubishi Electric Information Technology Center America, Inc. (ita)

Huifang Sun

Anthony Vetro

Ajay Divakaran

Tommy C Poon

Joel Walter Zdepski

Jun Xin

Hao-Song Kong

Tihao Chiang

Emin Martinian

Wilson Kwok

Yao Rong Wang

Bede Liu

Sun-Yuan Kung

Alexander Behrens

Ximin Zhang

Jay Bao

Kadir A Peker

Peng Yin

I-Jong Lin

Hiroshi Ito

Max Chien

Fatih M Porikli

Dong Tian

Shih-Fu Chang

Robert Cohen

Yao Nie

Wei-Ying Kung

Sehoon Yea

Ya-Qin Zhang

Bangalore S Manjunath

Yun-Qing Shi

Hae-Kwang Kim

Xinding Sun

Chung-Neng Wang

Ngai-Man Cheung

Kamil M Uz

Manoranjan D Jesudoss

Vinod Vijayalekshmi Vasudevan

Chul-soo Park

Peng Xu

Lexing Xie

Ganesh Rattinassababady

Hyundoo Shin

Paul DaGraca

Onur G Guleyruz

Yen-Kuang Chen

Yao-Chung Lin

Minghui Xia

A method processes keypoint trajectories in a video, wherein the keypoint trajectories describe motion of a plurality of keypoints across pictures of the video over time, by first acquiring the video of a scene using a camera. Keypoints and associated feature descriptors are detected in each picture. The keypoints and associated features descriptors are matched between neighboring pictures to generate keypoint trajectories. Then, the keypoint trajectories are coded predictively into a bitstream, which is outputted.

Method and apparatus for keypoint trajectory coding on compact descriptor for video analysis

A bitstream includes coded pictures, and split-flags for generating a transform tree. The bit stream is a partitioning of coding units (CUs) into Prediction Units (PUs). The transform tree is generated according to the split-flags. Nodes in the transform tree represent transform units (TU) associated with the CUs. The generation splits each TU only if the corresponding split-flag is set. For each PU that includes multiple TUs, the multiple TUs are merged into a larger TU, and the transform tree is modified according to the splitting and merging. Then, data contained in each PU can be decoded using the TVs associated with the PU according to the transform tree.

Method for coding pictures using hierarchical transform units

A quality of a virtual image for a synthetic viewpoint in a 3D scene is determined. The 3D scene is acquired by texture images, and each texture image is associated with a depth image acquired by a camera arranged at a real viewpoint. A texture noise power is based on the acquired texture images and reconstructed texture images corresponding to a virtual texture image. A depth noise power is based on the depth images and reconstructed depth images corresponding to a virtual depth image. The quality of the virtual image is based on a combination of the texture noise power and the depth noise power, and the virtual image is rendered from the reconstructed texture images and the reconstructed depth images.

Method for modeling and estimating rendering errors in virtual images

A bitstream includes coded pictures, and split-flags for generating a transform tree. The bit stream is a partitioning of coding units (CUs) into Prediction Units (PUs). The transform tree is generated according to the split-flags. Nodes in the transform tree represent transform units (TU) associated with the CUs. The generation splits each TU only if the corresponding split-flag is set. For each PU that includes multiple TUs, the multiple TUs are merged into a larger TU, and the transform tree is modified according to the splitting and merging. Then, data contained in each PU can be decoded using the TUs associated with the PU according to the transform tree.

Multiview videos are acquired of a scene with corresponding cameras arranged at poses, such that there is view overlap between any pair of cameras. V-frames are generated from the multiview videos. The V-frames are encoded using only spatial prediction. Then, the V-frames are inserted periodically in an encoded bit stream to provide random temporal access to the multiview videos. Additional view dependency information enables the decoding of a reduced number of frames prior to accessing randomly a target frame for a specified view and time, and decoding the target frame. The method also decodes multiview videos by maintaining a reference picture list for a current frame of a plurality of multiview videos, and predicting each current frame of the plurality of multiview videos according to reference pictures indexed by the associated reference picture list.

Method and system for decoding multiview videos with prediction dependencies

A method randomly accesses multiview videos. Multiview videos are acquired of a scene with corresponding cameras arranged at poses, such that there is view overlap between any pair of cameras. V-frames are generated from the multiview videos. The V-frames are encoded using only spatial prediction. Then, the V-frames are inserted periodically in an encoded bit stream to provide random temporal access to the multiview videos. Additional view dependency information enables the decoding of a reduced number of frames prior to accessing randomly a target frame for a specified view and time, and decoding the target frame.

Method and system for randomly accessing multiview videos with known prediction dependency

A system and method synthesizes multiview videos. Multiview videos are acquired of a scene with corresponding cameras arranged at a poses such that there is view overlap between any pair of cameras. A synthesized multiview video is generated from the acquired multiview videos for a virtual camera. A reference picture list is maintained for each current frame of each of the multiview videos and the synthesized video. The reference picture list indexes temporal reference pictures and spatial reference pictures of the acquired multiview videos and the synthesized reference pictures of the synthesized multiview video. Then, each current frame of the multiview videos is predicted according to reference pictures indexed by the associated reference picture list during encoding and decoding.

Method and system for synthesizing multiview videos

A method randomly accesses multiview videos. Multiview videos are acquired of a scene with corresponding cameras arranged at poses, such that there is view overlap between any pair of cameras. V-frames are generated from the multiview videos. The V-frames are encoded using only spatial prediction. Then, the V-frames are inserted periodically in an encoded bitstream to provide random temporal access to the multiview videos.

Method for randomly accessing multiview videos

A system and method manages multiview videos. A reference picture list is maintained for each current frame of multiple multiview videos. The reference picture list indexes temporal reference pictures, spatial reference pictures and synthesized reference pictures of the multiview videos. Then, each current frame of the multiview videos is predicted according to reference pictures indexed by the associated reference picture list during encoding and decoding.

Method and system for managing reference pictures in multiview videos

A method acquires compressed videos. Intra-, or inter-frames of each compressed video are acquired at a fixed sampling rate. Joint analysis is applied concurrently and in parallel to the compressed videos to determine a variable and non-uniform temporal sampling rate for each compressed video so that a combined distortion is minimized and a combined frame rate constraint is satisfied. Each compressed video is then sampled at the associated variable and non-uniform temporal sampling rate to produce output compressed videos having variable temporal resolutions.

Resource-constrained sampling of multiple compressed videos

A method and system processes a compressed input video. The compressed input video is processed to produce an interlaced picture, and macroblock coding information of the input video. The interlaced picture has a first spatial resolution, and a top-field and a bottom-field. The top-field and the bottom-field of the interlaced picture are filtered adaptively according to the macroblock coding information to produce a progressive picture with a second spatial resolution less than the first spatial resolution.

System and method for joint de-interlacing and down-sampling using adaptive frame and field filtering

A method filters pixels in an image, by first partitioning the image into blocks. Edge block are identified. A variance of an intensity for each pixel in each edge block is determined. Then, each pixel in each edge block is filtered with a filter that is dependant on the variance of the pixel.

System and method for filtering artifacts in images

A method conceals errors in an infra-frame of compressed video. The intra-frame is decoded to multiple macroblocks. Each macroblock including pixels arranged in a rectangular array. A lost macroblock is identified during the decoding. Pixels along an outer boundary of the lost macroblock are concealed from nearest candidate pixels along outer boundaries of macroblocks immediately adjacent to the lost macroblock. All other pixels in the lost macroblock are concealed from nearest candidate pixels selected from previously concealed pixels in the lost macroblock.

Error concealing decoding method of intra-frames of compressed videos

A method transcodes a compressed multi-layer video bitstream that includes a base layer bitstream and an enhancement layer bitstream. The base and enhancement layers are first partially decoded, and then the partially decoded signals are combined with a motion compensated signal yielding a combined signal. The combined signal is quantized into an output signal according to a quantization parameter, and the output signal is variable length encoded as a single layer bitstream. In a preprocessing step, the enhancement layer can be truncated according to rate control constraint, and the same constraints can also be used during the quantization.

Video transcoding of scalable multi-layer videos to single layer video

A method for generating a representation of multimedia content by first segmenting the multimedia content spatially and temporally to extract objects. Feature extraction is applied to the objects to produce semantic and syntactic attributes, relations, and a containment set of content entities. The content entities are coded to produce directed acyclic graphs of the content entities, where each directed acyclic graph represents a particular interpretation of the multimedia content. Attributes of each content entity are measured and the measured attributes are assigned to each corresponding content entity in the directed acyclic graphs to rank order the multimedia content.

Method for representing and comparing multimedia content according to rank

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Huifang Sun